{ "nodes": [ { "id": "tutorials/two-by-two-nash-explorer-tutorial", "title": "Building the 2×2 Nash Equilibrium Explorer — a Shiny tutorial", "url": "shiny/tutorials/two-by-two-nash-explorer-tutorial/", "topic": "shiny-tutorial", "tags": [ "nash-equilibrium", "interactive", "bimatrix-games" ], "labels": [ "shiny-app", "foundational-tool" ], "date": "2026-05-08", "year": 2026, "summary": "Step-by-step tutorial for building an interactive Shiny app that computes and visualizes Nash equilibria for arbitrary 2×2 bimatrix games, with best-response plots and expected payoff surfaces." }, { "id": "ai-ml-foundations-and-applications/gans-minimax-game", "title": "Generative adversarial networks as minimax games", "url": "tutorials/ai-ml-foundations-and-applications/gans-minimax-game/", "topic": "ai-ml-foundations-and-applications", "tags": [ "gans", "minimax", "zero-sum" ], "labels": [ "ai-ml", "minimax-applications" ], "date": "2026-05-08", "year": 2026, "summary": "Frame GANs as two-player zero-sum games in R, implement a simple GAN training loop for 1D data, visualise the generator-discriminator dynamics, and connect the equilibrium to Nash equilibrium theory." }, { "id": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "title": "Automated Mechanism Design for Optimal Auctions", "url": "tutorials/ai-ml-foundations-and-applications/mechanism-design-ml-auctions/", "topic": "ai-ml-foundations-and-applications", "tags": [ "mechanism-design", "auctions" ], "labels": [ "mechanism-design", "ml" ], "date": "2026-05-08", "year": 2026, "summary": "Training a data-driven auction mechanism using gradient-free optimisation in pure R — learning payment rules from bidder profiles, enforcing incentive compatibility and individual rationality, and benchmarking against Myerson's optimal auction." }, { "id": "ai-ml-foundations-and-applications/multi-armed-bandits-exploration", "title": "Multi-armed bandits and the exploration-exploitation trade-off", "url": "tutorials/ai-ml-foundations-and-applications/multi-armed-bandits-exploration/", "topic": "ai-ml-foundations-and-applications", "tags": [ "multi-armed-bandits", "reinforcement-learning", "exploration-exploitation" ], "labels": [ "bandits", "ucb1", "thompson-sampling", "epsilon-greedy" ], "date": "2026-05-08", "year": 2026, "summary": "Implementation and analysis of bandit algorithms including epsilon-greedy, UCB1, and Thompson sampling, framed as single-agent games against nature with regret analysis, Bayesian updating, and interactive performance comparisons." }, { "id": "ai-ml-foundations-and-applications/perceptron-to-deep-learning-historical-r-implementation", "title": "From Perceptron to deep learning — a historical R implementation", "url": "tutorials/ai-ml-foundations-and-applications/perceptron-to-deep-learning-historical-r-implementation/", "topic": "ai-ml-foundations-and-applications", "tags": [ "neural-networks", "perceptron", "deep-learning", "historical" ], "labels": [ "ai-ml-history", "neural-networks" ], "date": "2026-05-08", "year": 2026, "summary": "Trace the evolution of neural networks from Rosenblatt's 1958 Perceptron through the Minsky-Papert critique to backpropagation and modern deep learning, implementing key milestones in R." }, { "id": "ai-ml-foundations-and-applications/shap-values-cooperative-games", "title": "SHAP Values as Shapley Values — Cooperative Game Theory Meets Explainable AI", "url": "tutorials/ai-ml-foundations-and-applications/shap-values-cooperative-games/", "topic": "ai-ml-foundations-and-applications", "tags": [ "shap", "shapley-value" ], "labels": [ "machine-learning", "cooperative-games" ], "date": "2026-05-08", "year": 2026, "summary": "Demonstrate that SHAP (SHapley Additive exPlanations) is a direct application of the Shapley value from cooperative game theory, computing exact Shapley values for a 4-feature prediction model by enumerating all coalitions and verifying the efficiency, symmetry, dummy, and additivity axioms in R." }, { "id": "auction-theory-deep-dive/all-pay-auction-lobbying", "title": "All-pay auctions and the economics of lobbying", "url": "tutorials/auction-theory-deep-dive/all-pay-auction-lobbying/", "topic": "auction-theory-deep-dive", "tags": [ "all-pay-auction", "lobbying", "rent-seeking" ], "labels": [ "auction-theory", "political-economy" ], "date": "2026-05-08", "year": 2026, "summary": "Analyse the all-pay auction in R where all bidders pay their bids regardless of winning, derive the symmetric equilibrium with uniform values, and apply the model to lobbying, rent-seeking, and political campaigns." }, { "id": "auction-theory-deep-dive/common-value-winners-curse", "title": "Common-value auctions and the winner's curse", "url": "tutorials/auction-theory-deep-dive/common-value-winners-curse/", "topic": "auction-theory-deep-dive", "tags": [ "common-value-auctions", "winners-curse", "information-economics" ], "labels": [ "auction-theory", "information-economics" ], "date": "2026-05-08", "year": 2026, "summary": "Derive, simulate, and visualize the winner's curse in common-value auctions: why naive bidding leads to systematic overpayment, and how rational bidders correct for the informational content of winning." }, { "id": "auction-theory-deep-dive/english-ascending-auction", "title": "The English Ascending Auction", "url": "tutorials/auction-theory-deep-dive/english-ascending-auction/", "topic": "auction-theory-deep-dive", "tags": [ "english-auction", "ascending-auction", "dominant-strategy" ], "labels": [ "auctions", "mechanism-design" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the button auction (Japanese) model of the English ascending auction, prove that bidding up to one's value is weakly dominant, derive expected revenue, and compare with sealed-bid formats under uniform and log-normal value distributions." }, { "id": "auction-theory-deep-dive/first-price-sealed-bid", "title": "First-price sealed-bid auction — equilibrium bidding strategies", "url": "tutorials/auction-theory-deep-dive/first-price-sealed-bid/", "topic": "auction-theory-deep-dive", "tags": [ "first-price-auction", "bayesian-nash", "bid-shading" ], "labels": [ "auction-theory", "equilibrium-bidding" ], "date": "2026-05-08", "year": 2026, "summary": "Derive the Bayesian Nash equilibrium of the first-price sealed-bid auction in R, show bid-shading as a function of the number of bidders, and compare revenue across auction formats." }, { "id": "auction-theory-deep-dive/gsp-auction", "title": "GSP auction for online advertising", "url": "tutorials/auction-theory-deep-dive/gsp-auction/", "topic": "auction-theory-deep-dive", "tags": [ "gsp-auction", "online-advertising", "mechanism-design" ], "labels": [ "auction-theory", "mechanism-design" ], "date": "2026-05-08", "year": 2026, "summary": "Analyze the Generalized Second-Price auction used by search engines: compute VCG payments vs GSP equilibrium payments, show that GSP is not truthful, and characterize locally envy-free equilibria." }, { "id": "auction-theory-deep-dive/revenue-equivalence", "title": "Revenue equivalence theorem", "url": "tutorials/auction-theory-deep-dive/revenue-equivalence/", "topic": "auction-theory-deep-dive", "tags": [ "revenue-equivalence", "auction-formats", "mechanism-design" ], "labels": [ "auction-theory", "mechanism-design" ], "date": "2026-05-08", "year": 2026, "summary": "State, prove, and numerically verify the Revenue Equivalence Theorem across four standard auction formats — first-price, second-price, Dutch, and English — with simulations showing when RET holds and when it breaks down." }, { "id": "bayesian-methods/auction-common-value-estimation", "title": "Bayesian Estimation in Common-Value Auctions and the Winner's Curse", "url": "tutorials/bayesian-methods/auction-common-value-estimation/", "topic": "bayesian-methods", "tags": [ "auction-theory" ], "labels": [ "bayesian-methods", "auction-theory" ], "date": "2026-05-08", "year": 2026, "summary": "Model common-value auctions with noisy signals, derive optimal bids accounting for the winner's curse, and simulate the devastating effect of naive bidding on expected profits." }, { "id": "bayesian-methods/auction-optimal-reserve-prices", "title": "Optimal reserve prices in auctions — Myerson's revenue-maximising design", "url": "tutorials/bayesian-methods/auction-optimal-reserve-prices/", "topic": "bayesian-methods", "tags": [ "auction-design", "reserve-prices", "myerson" ], "labels": [ "auction-theory", "mechanism-design" ], "date": "2026-05-08", "year": 2026, "summary": "Derive Myerson's optimal reserve price for sealed-bid auctions, implement revenue comparisons across uniform and non-uniform value distributions, and visualize the revenue gains from optimal auction design in R." }, { "id": "bayesian-methods/bayesian-games-incomplete-information", "title": "Bayesian games — strategic interaction under incomplete information", "url": "tutorials/bayesian-methods/bayesian-games-incomplete-information/", "topic": "bayesian-methods", "tags": [ "bayesian-games", "incomplete-information", "bayes-nash" ], "labels": [ "bayesian-gt", "equilibrium-concepts" ], "date": "2026-05-08", "year": 2026, "summary": "Formalise games of incomplete information in R, compute Bayes-Nash equilibria for type-dependent strategies, and visualize how private information shapes equilibrium behaviour." }, { "id": "bayesian-methods/global-games-coordination", "title": "Global games and coordination under private information", "url": "tutorials/bayesian-methods/global-games-coordination/", "topic": "bayesian-methods", "tags": [ "global-games", "coordination", "incomplete-information" ], "labels": [ "bayesian-games", "equilibrium-selection" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the Carlsson-van Damme and Morris-Shin global games framework in R, showing how private noisy signals about fundamentals resolve equilibrium multiplicity in coordination games through threshold strategies." }, { "id": "bayesian-methods/information-design-persuasion", "title": "Bayesian persuasion and information design", "url": "tutorials/bayesian-methods/information-design-persuasion/", "topic": "bayesian-methods", "tags": [ "information-design", "bayesian-persuasion", "signalling" ], "labels": [ "information-economics", "mechanism-design" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the Kamenica-Gentzkow (2011) Bayesian persuasion model in R, computing optimal signal structures via concavification for the binary-state prosecutor-judge example." }, { "id": "behavioral-economics/endowment-effect-exchange", "title": "The Endowment Effect and Exchange Asymmetries", "url": "tutorials/behavioral-economics/endowment-effect-exchange/", "topic": "behavioral-economics", "tags": [ "endowment-effect" ], "labels": [ "behavioral-economics", "prospect-theory" ], "date": "2026-05-08", "year": 2026, "summary": "Model the endowment effect using loss aversion from prospect theory, simulate the Knetsch mug-pen exchange experiment, and show how loss aversion reduces trading volume below the efficient Coasian prediction." }, { "id": "behavioral-economics/hyperbolic-discounting-games", "title": "Hyperbolic discounting and time-inconsistent strategic behaviour", "url": "tutorials/behavioral-economics/hyperbolic-discounting-games/", "topic": "behavioral-economics", "tags": [ "hyperbolic-discounting", "time-inconsistency", "commitment" ], "labels": [ "behavioral-game-theory", "intertemporal-choice" ], "date": "2026-05-08", "year": 2026, "summary": "Model quasi-hyperbolic (beta,delta) preferences in strategic settings, find Markov perfect equilibria of intrapersonal games, and compare exponential vs hyperbolic discounters in repeated interactions." }, { "id": "behavioral-economics/mental-accounting-thaler", "title": "Mental accounting and strategic framing", "url": "tutorials/behavioral-economics/mental-accounting-thaler/", "topic": "behavioral-economics", "tags": [ "mental-accounting", "framing-effects", "transaction-utility" ], "labels": [ "behavioral-economics", "framing" ], "date": "2026-05-08", "year": 2026, "summary": "Thaler's mental accounting framework applied to strategic pricing: how framing purchases as bundled versus separated, or as gains versus reduced losses, systematically alters willingness to pay, modelled through transaction utility theory and simulated seller-buyer interactions." }, { "id": "behavioral-economics/nudge-libertarian-paternalism", "title": "Nudge theory and libertarian paternalism", "url": "tutorials/behavioral-economics/nudge-libertarian-paternalism/", "topic": "behavioral-economics", "tags": [ "nudge-theory", "choice-architecture", "default-effects" ], "labels": [ "behavioral-economics", "policy-design" ], "date": "2026-05-08", "year": 2026, "summary": "Thaler and Sunstein's nudge framework modelled as a game between a benevolent choice architect and boundedly rational agents, with simulations of default effects on organ donation and retirement savings." }, { "id": "behavioral-economics/prospect-theory-kahneman-tversky", "title": "Prospect theory — loss aversion and probability weighting", "url": "tutorials/behavioral-economics/prospect-theory-kahneman-tversky/", "topic": "behavioral-economics", "tags": [ "prospect-theory", "loss-aversion" ], "labels": [ "behavioral-econ", "decision-theory" ], "date": "2026-05-08", "year": 2026, "summary": "Implement Kahneman & Tversky's prospect theory value function and probability weighting in R, compare expected utility vs prospect theory predictions for common gambles, and visualize the S-shaped value function interactively." }, { "id": "behavioral-gt/level-k-cognitive-hierarchy", "title": "Level-k thinking and cognitive hierarchy — bounded rationality in strategic games", "url": "tutorials/behavioral-gt/level-k-cognitive-hierarchy/", "topic": "behavioral-gt", "tags": [ "level-k", "cognitive-hierarchy", "bounded-rationality" ], "labels": [ "behavioral-gt", "experimental-economics" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the level-k model and Camerer-Ho-Chong cognitive hierarchy for the p-beauty contest, simulate heterogeneous populations, and visualize convergence to Nash equilibrium as strategic sophistication increases." }, { "id": "behavioral-gt/public-goods-punishment", "title": "The public goods game with punishment — sustaining cooperation through costly enforcement", "url": "tutorials/behavioral-gt/public-goods-punishment/", "topic": "behavioral-gt", "tags": [ "public-goods", "punishment", "cooperation" ], "labels": [ "behavioral-experiments", "cooperation" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the public goods game with and without costly punishment in R, simulate contribution dynamics with heterogeneous agent types, and reproduce the Fehr and Gaechter finding that punishment sustains cooperation where standard theory predicts free-riding." }, { "id": "behavioral-gt/quantal-response-equilibrium", "title": "Quantal response equilibrium — bridging rationality and noise", "url": "tutorials/behavioral-gt/quantal-response-equilibrium/", "topic": "behavioral-gt", "tags": [ "quantal-response-equilibrium", "bounded-rationality", "experimental-games" ], "labels": [ "behavioral-gt", "equilibrium-concepts" ], "date": "2026-05-08", "year": 2026, "summary": "Implement quantal response equilibrium (QRE) in R, derive the logit equilibrium for 2x2 games, trace the QRE correspondence from uniform randomisation to Nash equilibrium, and fit QRE to experimental data from coordination and asymmetric games." }, { "id": "behavioral-gt/social-preferences-fehr-schmidt", "title": "Fehr-Schmidt inequality aversion: modelling fairness in games", "url": "tutorials/behavioral-gt/social-preferences-fehr-schmidt/", "topic": "behavioral-gt", "tags": [ "social-preferences", "inequality-aversion" ], "labels": [ "behavioral", "social-preferences" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the Fehr-Schmidt model of inequality aversion, where players experience disutility from both advantageous and disadvantageous inequality, and apply it to the ultimatum, dictator, and public goods games." }, { "id": "behavioral-gt/ultimatum-game-fairness", "title": "The ultimatum game — fairness, rejection, and bounded rationality", "url": "tutorials/behavioral-gt/ultimatum-game-fairness/", "topic": "behavioral-gt", "tags": [ "ultimatum-game", "fairness", "bounded-rationality" ], "labels": [ "behavioral-experiments", "fairness-norms" ], "date": "2026-05-08", "year": 2026, "summary": "Analyse the ultimatum game in R, contrasting the subgame-perfect equilibrium prediction with experimental evidence on fairness norms, and implementing inequality aversion models that explain rejection behaviour." }, { "id": "case-studies/climate-coalition-formation", "title": "Climate coalition formation — cooperative game theory and the stability of international agreements", "url": "tutorials/case-studies/climate-coalition-formation/", "topic": "case-studies", "tags": [ "cooperative-games", "coalition-formation", "climate-policy" ], "labels": [ "cooperative-gt", "policy-applications" ], "date": "2026-05-08", "year": 2026, "summary": "Model international climate agreements as a cooperative partition function game, compute Shapley values for responsibility allocation, analyse coalition stability and free-riding incentives, and visualize why the grand coalition is unstable." }, { "id": "case-studies/opec-cartel-oligopoly", "title": "OPEC as a cartel — oligopoly theory applied to oil markets", "url": "tutorials/case-studies/opec-cartel-oligopoly/", "topic": "case-studies", "tags": [ "oligopoly", "cartel", "opec" ], "labels": [ "industrial-organization", "applied-game-theory" ], "date": "2026-05-08", "year": 2026, "summary": "Model OPEC as a repeated Cournot oligopoly with heterogeneous producers, compute Nash and cartel equilibria, analyse deviation incentives, and determine the critical discount factor for cartel sustainability." }, { "id": "case-studies/spectrum-auction-design", "title": "Spectrum auction design — from theory to billions in revenue", "url": "tutorials/case-studies/spectrum-auction-design/", "topic": "case-studies", "tags": [ "spectrum-auctions", "mechanism-design" ], "labels": [ "auction-design", "policy-case-study" ], "date": "2026-05-08", "year": 2026, "summary": "Analyse the FCC spectrum auctions as a mechanism design case study, model simultaneous ascending auctions and combinatorial bidding in R, and visualize revenue outcomes across major US spectrum sales." }, { "id": "case-studies/spectrum-auctions-policy", "title": "Spectrum Auction Design: A Case Study in Applied Mechanism Design", "url": "tutorials/case-studies/spectrum-auctions-policy/", "topic": "case-studies", "tags": [ "auction-design" ], "labels": [ "case-studies", "auction-design" ], "date": "2026-05-08", "year": 2026, "summary": "Simulate key challenges in spectrum auction design --- combinatorial valuations, budget constraints, and market concentration --- and compare simultaneous ascending auctions with combinatorial clock auctions." }, { "id": "case-studies/tragedy-of-the-commons", "title": "Tragedy of the commons — game-theoretic analysis", "url": "tutorials/case-studies/tragedy-of-the-commons/", "topic": "case-studies", "tags": [ "commons-dilemma", "public-goods", "institutional-design" ], "labels": [ "case-studies", "institutional-design" ], "date": "2026-05-08", "year": 2026, "summary": "Hardin's tragedy of the commons modelled as an N-player commons dilemma with continuous extraction, comparing Nash equilibrium over-extraction to the social optimum and simulating Ostrom's institutional design principles." }, { "id": "causal-inference/difference-in-differences-strategic", "title": "Difference-in-differences with strategic agents", "url": "tutorials/causal-inference/difference-in-differences-strategic/", "topic": "causal-inference", "tags": [ "difference-in-differences", "strategic-interaction", "parallel-trends" ], "labels": [ "causal-inference", "econometrics" ], "date": "2026-05-08", "year": 2026, "summary": "Applying the difference-in-differences estimator to settings where treatment alters a strategic equilibrium, demonstrating how agents' endogenous responses can violate the parallel trends assumption and bias causal estimates." }, { "id": "causal-inference/instrumental-variables-game-theory", "title": "Instrumental variables for causal effects in strategic settings", "url": "tutorials/causal-inference/instrumental-variables-game-theory/", "topic": "causal-inference", "tags": [ "instrumental-variables", "endogeneity" ], "labels": [ "causal-methods", "applied-econometrics" ], "date": "2026-05-08", "year": 2026, "summary": "Use instrumental variable methods to estimate causal effects when strategic interaction creates endogeneity, implement two-stage least squares (2SLS) in R, and apply the approach to a game-theoretic model of market entry." }, { "id": "causal-inference/instrumental-variables-strategic", "title": "Instrumental variables in strategic settings", "url": "tutorials/causal-inference/instrumental-variables-strategic/", "topic": "causal-inference", "tags": [ "instrumental-variables", "endogeneity", "strategic-interaction" ], "labels": [ "iv-estimation", "2sls", "simultaneity", "weak-instruments" ], "date": "2026-05-08", "year": 2026, "summary": "An application of instrumental variables methods to estimate causal effects in games where strategic actions are endogenous, covering simultaneity bias, instrument validity, two-stage least squares with simulated game data, and weak instruments diagnostics." }, { "id": "causal-inference/regression-discontinuity-strategic", "title": "Regression discontinuity in strategic settings", "url": "tutorials/causal-inference/regression-discontinuity-strategic/", "topic": "causal-inference", "tags": [ "regression-discontinuity", "strategic-manipulation", "treatment-effects" ], "labels": [ "causal-inference", "regression-discontinuity" ], "date": "2026-05-08", "year": 2026, "summary": "Regression discontinuity design applied to games: how a regulatory threshold creates a discontinuity in strategic incentives, with local polynomial estimation of the treatment effect and a McCrary density test to detect strategic manipulation of the running variable." }, { "id": "causal-inference/synthetic-control-strategic", "title": "Synthetic Control Methods for Strategic Policy Interventions", "url": "tutorials/causal-inference/synthetic-control-strategic/", "topic": "causal-inference", "tags": [ "synthetic-control", "policy-evaluation" ], "labels": [ "causal-inference", "policy-evaluation" ], "date": "2026-05-08", "year": 2026, "summary": "Apply the synthetic control method to estimate the causal effect of a competition policy change in a strategic environment, using constrained optimisation to construct counterfactual outcomes from untreated regions." }, { "id": "classical-games/bank-runs-coordination", "title": "Bank runs as a coordination game — the Diamond-Dybvig model", "url": "tutorials/classical-games/bank-runs-coordination/", "topic": "classical-games", "tags": [ "coordination", "bank-runs", "financial-economics" ], "labels": [ "canonical-games", "coordination-games" ], "date": "2026-05-08", "year": 2026, "summary": "Model bank runs as a coordination game using the Diamond-Dybvig framework in R, showing the Stag Hunt structure, deposit insurance as equilibrium selection, and contagion dynamics with N depositors." }, { "id": "classical-games/battle-of-the-sexes", "title": "Battle of the Sexes — coordination with conflicting preferences", "url": "tutorials/classical-games/battle-of-the-sexes/", "topic": "classical-games", "tags": [ "battle-of-the-sexes", "coordination", "multiple-equilibria" ], "labels": [ "canonical-games", "coordination-games" ], "date": "2026-05-08", "year": 2026, "summary": "Analyse the Battle of the Sexes game formally in R, find all Nash equilibria (two pure + one mixed), and visualize the coordination problem with best-response correspondences." }, { "id": "classical-games/chicken-game-brinkmanship", "title": "The game of Chicken and the art of brinkmanship", "url": "tutorials/classical-games/chicken-game-brinkmanship/", "topic": "classical-games", "tags": [ "chicken", "brinkmanship", "mixed-strategy" ], "labels": [ "classical-games", "conflict" ], "date": "2026-05-08", "year": 2026, "summary": "Analyse the Chicken game in R, compute all Nash equilibria including the mixed-strategy equilibrium, model brinkmanship as a commitment device, and apply to nuclear deterrence, traffic merging, and corporate competition." }, { "id": "classical-games/chicken-hawk-dove", "title": "Chicken / Hawk-Dove — brinkmanship and anti-coordination", "url": "tutorials/classical-games/chicken-hawk-dove/", "topic": "classical-games", "tags": [ "chicken", "hawk-dove", "anti-coordination", "ess" ], "labels": [ "canonical-games", "conflict-games" ], "date": "2026-05-08", "year": 2026, "summary": "Analyse the Chicken (Hawk-Dove) game in R, computing pure and mixed Nash equilibria, exploring the evolutionary stable strategy, and connecting to models of escalation and conflict." }, { "id": "classical-games/colonel-blotto", "title": "The Colonel Blotto game — resource allocation across battlefields", "url": "tutorials/classical-games/colonel-blotto/", "topic": "classical-games", "tags": [ "blotto", "resource-allocation", "mixed-strategies" ], "labels": [ "canonical-games", "zero-sum-games" ], "date": "2026-05-08", "year": 2026, "summary": "Analyse the Colonel Blotto game in R, exploring optimal resource allocation across multiple battlefields, mixed-strategy equilibria, and applications to political campaigns and military strategy." }, { "id": "classical-games/el-farol-bar-problem", "title": "The El Farol Bar Problem", "url": "tutorials/classical-games/el-farol-bar-problem/", "topic": "classical-games", "tags": [ "bounded-rationality", "agent-based-model", "minority-game" ], "labels": [ "classical", "simulation" ], "date": "2026-05-08", "year": 2026, "summary": "Simulating Arthur's (1994) El Farol Bar problem with heterogeneous prediction strategies, analysing attendance oscillations, and connecting to minority games and market ecology." }, { "id": "classical-games/iterated-prisoners-dilemma-axelrod", "title": "The iterated Prisoner's Dilemma — Axelrod's tournaments", "url": "tutorials/classical-games/iterated-prisoners-dilemma-axelrod/", "topic": "classical-games", "tags": [ "prisoners-dilemma", "iterated-games", "axelrod", "cooperation" ], "labels": [ "canonical-games", "repeated-games" ], "date": "2026-05-08", "year": 2026, "summary": "Replicate Robert Axelrod's classic 1980 computer tournaments for the iterated Prisoner's Dilemma in R, with round-robin scoring, strategy comparison, and evolutionary dynamics." }, { "id": "classical-games/matching-pennies-experimental", "title": "Matching Pennies — Theory Meets Experimental Evidence", "url": "tutorials/classical-games/matching-pennies-experimental/", "topic": "classical-games", "tags": [ "matching-pennies", "experimental-economics" ], "labels": [ "canonical-games", "experimental-games" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the classic zero-sum matching pennies game with its unique mixed Nash equilibrium, then simulate experimental play using bounded rationality models including epsilon-greedy, fictitious play, and reinforcement learning to study convergence and exploitable patterns in R." }, { "id": "classical-games/matching-pennies", "title": "Matching Pennies — the simplest zero-sum game", "url": "tutorials/classical-games/matching-pennies/", "topic": "classical-games", "tags": [ "matching-pennies", "zero-sum", "mixed-strategy" ], "labels": [ "canonical-games", "zero-sum-games" ], "date": "2026-05-08", "year": 2026, "summary": "Analyse Matching Pennies as the canonical two-player zero-sum game with a unique mixed-strategy Nash equilibrium, implementing minimax strategies and expected payoff calculations in R." }, { "id": "classical-games/prisoners-dilemma-formal", "title": "The Prisoner's Dilemma — formal setup and dominant strategy analysis", "url": "tutorials/classical-games/prisoners-dilemma-formal/", "topic": "classical-games", "tags": [ "prisoners-dilemma", "dominant-strategy", "social-dilemma" ], "labels": [ "canonical-games", "social-dilemmas" ], "date": "2026-05-08", "year": 2026, "summary": "Define the one-shot Prisoner's Dilemma formally, prove that mutual defection is the unique dominant-strategy equilibrium, and explore how payoff parameters affect the tension between individual and collective rationality." }, { "id": "classical-games/stag-hunt", "title": "The Stag Hunt — coordination, trust, and risk dominance", "url": "tutorials/classical-games/stag-hunt/", "topic": "classical-games", "tags": [ "stag-hunt", "coordination", "risk-dominance" ], "labels": [ "canonical-games", "coordination-games" ], "date": "2026-05-08", "year": 2026, "summary": "Analyse the Stag Hunt as a coordination game with Pareto-ranked equilibria in R, comparing payoff dominance and risk dominance, with basin-of-attraction analysis." }, { "id": "classical-games/war-of-attrition-sealed", "title": "The Sealed-Bid War of Attrition", "url": "tutorials/classical-games/war-of-attrition-sealed/", "topic": "classical-games", "tags": [ "war-of-attrition", "all-pay-auction", "bayesian-nash-equilibrium" ], "labels": [ "auctions", "classical" ], "date": "2026-05-08", "year": 2026, "summary": "Analyse the sealed-bid war of attrition as an all-pay second-price auction, derive the symmetric Bayesian Nash equilibrium with exponential bidding strategies for uniform private values, and compare revenue and surplus with the standard all-pay auction." }, { "id": "cooperative-gt/bankruptcy-game-talmud", "title": "The bankruptcy game and the Talmudic rule", "url": "tutorials/cooperative-gt/bankruptcy-game-talmud/", "topic": "cooperative-gt", "tags": [ "bankruptcy-game", "talmud", "fair-division" ], "labels": [ "cooperative-gt", "fair-division" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the contested garment principle and the Talmudic bankruptcy rule in R, show their connection to the nucleolus of cooperative games, and compare with proportional and constrained equal awards division methods." }, { "id": "cooperative-gt/coalition-formation-hedonic", "title": "Hedonic coalition formation games", "url": "tutorials/cooperative-gt/coalition-formation-hedonic/", "topic": "cooperative-gt", "tags": [ "coalition-formation", "hedonic-games", "matching" ], "labels": [ "cooperative-games", "matching-theory" ], "date": "2026-05-08", "year": 2026, "summary": "Implement hedonic coalition formation with individual and Nash stability concepts in R, applied to a roommate matching example with 6 players." }, { "id": "cooperative-gt/core-stability", "title": "Core stability in cooperative games — unblocked allocations and the Bondareva-Shapley theorem", "url": "tutorials/cooperative-gt/core-stability/", "topic": "cooperative-gt", "tags": [ "core", "coalitional-games", "linear-programming" ], "labels": [ "cooperative-solutions", "stability" ], "date": "2026-05-08", "year": 2026, "summary": "Define the core of a cooperative game, check non-emptiness via linear programming and the Bondareva-Shapley theorem, compute core allocations for classic games, and visualize the core as a region in the simplex for three-player games." }, { "id": "cooperative-gt/rubinstein-alternating-offers", "title": "Rubinstein's alternating-offers bargaining game", "url": "tutorials/cooperative-gt/rubinstein-alternating-offers/", "topic": "cooperative-gt", "tags": [ "bargaining", "rubinstein", "subgame-perfection" ], "labels": [ "bargaining-theory", "cooperative-gt" ], "date": "2026-05-08", "year": 2026, "summary": "Implement Rubinstein's infinite-horizon alternating-offers model in R, derive the unique subgame-perfect equilibrium as a function of discount factors, and visualise how patience determines bargaining power." }, { "id": "cooperative-gt/shapley-shubik-power", "title": "The Shapley-Shubik power index for weighted voting games", "url": "tutorials/cooperative-gt/shapley-shubik-power/", "topic": "cooperative-gt", "tags": [ "voting-power", "shapley-value" ], "labels": [ "cooperative-games", "voting" ], "date": "2026-05-08", "year": 2026, "summary": "Measure each voter's true power in weighted voting games using the Shapley-Shubik index, and discover why voting weight and voting power are fundamentally different." }, { "id": "cooperative-gt/shapley-value", "title": "The Shapley value — fair division of cooperative surplus", "url": "tutorials/cooperative-gt/shapley-value/", "topic": "cooperative-gt", "tags": [ "shapley-value", "fair-division", "coalitional-games" ], "labels": [ "cooperative-solutions", "fairness" ], "date": "2026-05-08", "year": 2026, "summary": "Derive the Shapley value axiomatically, implement it for arbitrary coalitional games in R, and visualize marginal contributions and fairness properties with interactive examples." }, { "id": "cooperative-gt/voting-power-indices", "title": "Voting power indices — when weight does not equal power", "url": "tutorials/cooperative-gt/voting-power-indices/", "topic": "cooperative-gt", "tags": [ "voting-power", "banzhaf", "shapley-shubik" ], "labels": [ "cooperative-solutions", "voting-games" ], "date": "2026-05-08", "year": 2026, "summary": "Compute the Banzhaf and Shapley-Shubik power indices for weighted voting games in R, apply them to the EU Council, UN Security Council, and US Electoral College, and visualize the divergence between voting weight and true voting power." }, { "id": "cryptography-and-gt/blockchain-consensus-game", "title": "Blockchain consensus as a game", "url": "tutorials/cryptography-and-gt/blockchain-consensus-game/", "topic": "cryptography-and-gt", "tags": [ "blockchain", "mining-game", "coalition-formation" ], "labels": [ "cryptography-and-gt", "mechanism-design" ], "date": "2026-05-08", "year": 2026, "summary": "Model Proof-of-Work mining as a strategic game among heterogeneous miners, analyse Nash equilibrium hash rate allocation, simulate 51% attack incentives as a coordination game, and explore mining pool formation through coalition game theory." }, { "id": "cryptography-and-gt/commitment-schemes-game-theory", "title": "Commitment schemes and strategic credibility", "url": "tutorials/cryptography-and-gt/commitment-schemes-game-theory/", "topic": "cryptography-and-gt", "tags": [ "commitment", "stackelberg-games", "mechanism-design" ], "labels": [ "commitment", "stackelberg", "credibility", "binding-mechanism" ], "date": "2026-05-08", "year": 2026, "summary": "An analysis of how cryptographic commitment schemes enable credible strategic commitments in games, connecting hash-based commitment protocols to Stackelberg leadership, the value of commitment, and equilibrium refinement through binding mechanisms." }, { "id": "cryptography-and-gt/secure-multi-party-computation", "title": "Secure multi-party computation as a game-theoretic problem", "url": "tutorials/cryptography-and-gt/secure-multi-party-computation/", "topic": "cryptography-and-gt", "tags": [ "secure-computation", "secret-sharing" ], "labels": [ "crypto-games", "protocol-design" ], "date": "2026-05-08", "year": 2026, "summary": "Model secure multi-party computation as a game where parties have private inputs and incentives to deviate, implement Shamir's secret sharing in R, and visualize threshold schemes and security guarantees interactively." }, { "id": "cryptography-and-gt/secure-multiparty-computation", "title": "Secure Multi-Party Computation and Game-Theoretic Incentives", "url": "tutorials/cryptography-and-gt/secure-multiparty-computation/", "topic": "cryptography-and-gt", "tags": [ "secure-computation", "mechanism-design" ], "labels": [ "cryptography", "mechanism-design" ], "date": "2026-05-08", "year": 2026, "summary": "Implement Shamir's secret sharing and a secure multi-party computation protocol for sealed-bid auctions in R, analysing how MPC enables commitment to truthful strategies and incentive compatibility." }, { "id": "cryptography-and-gt/zero-knowledge-proofs", "title": "Zero-knowledge proofs — game-theoretic foundations", "url": "tutorials/cryptography-and-gt/zero-knowledge-proofs/", "topic": "cryptography-and-gt", "tags": [ "zero-knowledge-proofs", "interactive-protocols", "computational-complexity" ], "labels": [ "cryptography-and-gt", "protocol-design" ], "date": "2026-05-08", "year": 2026, "summary": "Zero-knowledge proofs modelled as interactive games between a Prover and Verifier, with simulations of the graph colouring ZKP protocol demonstrating completeness, soundness, and zero-knowledge properties." }, { "id": "decision-theory/allais-paradox", "title": "The Allais paradox and expected utility violations", "url": "tutorials/decision-theory/allais-paradox/", "topic": "decision-theory", "tags": [ "allais-paradox", "expected-utility", "prospect-theory" ], "labels": [ "decision-theory", "behavioural-anomalies" ], "date": "2026-05-08", "year": 2026, "summary": "Demonstrate the Allais paradox as a systematic violation of the independence axiom in expected utility theory, implement EU calculations in R, and explore prospect theory's probability weighting as an explanation." }, { "id": "decision-theory/ambiguity-aversion-ellsberg", "title": "Ambiguity aversion and the Ellsberg paradox", "url": "tutorials/decision-theory/ambiguity-aversion-ellsberg/", "topic": "decision-theory", "tags": [ "ambiguity-aversion", "ellsberg-paradox", "maxmin-expected-utility" ], "labels": [ "decision-under-uncertainty", "behavioral-foundations" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the Ellsberg urn experiment in R, model ambiguity aversion using maxmin expected utility and alpha-MEU, and show how ambiguity affects strategic decisions and games with unknown opponent types." }, { "id": "decision-theory/expected-utility-foundations", "title": "Expected Utility Theory: The Axiomatic Foundations", "url": "tutorials/decision-theory/expected-utility-foundations/", "topic": "decision-theory", "tags": [ "expected-utility", "risk-aversion", "axioms" ], "labels": [ "theory", "foundations" ], "date": "2026-05-08", "year": 2026, "summary": "Implementing the von Neumann-Morgenstern axioms in R, verifying them with lottery objects, demonstrating the Allais and Ellsberg paradoxes, and calibrating CRRA and CARA utility functions via MLE." }, { "id": "decision-theory/expected-utility-vnm-axioms", "title": "Expected utility theory and the von Neumann–Morgenstern axioms", "url": "tutorials/decision-theory/expected-utility-vnm-axioms/", "topic": "decision-theory", "tags": [ "expected-utility", "vnm-axioms", "risk-aversion" ], "labels": [ "decision-foundations", "utility-theory" ], "date": "2026-05-08", "year": 2026, "summary": "Derive expected utility from the VNM axioms in R, demonstrate the representation theorem with numerical examples, and visualize risk attitudes through utility function curvature." }, { "id": "decision-theory/prospect-theory-reference-dependence", "title": "Reference dependence and loss aversion in games — how prospect theory reshapes equilibria", "url": "tutorials/decision-theory/prospect-theory-reference-dependence/", "topic": "decision-theory", "tags": [ "prospect-theory", "loss-aversion", "reference-dependence" ], "labels": [ "behavioral-gt", "equilibrium-concepts" ], "date": "2026-05-08", "year": 2026, "summary": "Recompute Nash equilibria when players evaluate payoffs through prospect theory's lens of reference dependence and loss aversion, and visualize how equilibrium structure shifts in the Stag Hunt as loss aversion varies." }, { "id": "decision-theory/savage-subjective-probability", "title": "Savage's Subjective Expected Utility: From Axioms to Beliefs", "url": "tutorials/decision-theory/savage-subjective-probability/", "topic": "decision-theory", "tags": [ "subjective-probability" ], "labels": [ "decision-theory", "bayesian-foundations" ], "date": "2026-05-08", "year": 2026, "summary": "Implement Savage's seven axioms of subjective expected utility, derive subjective probabilities from revealed preferences, and demonstrate the Ellsberg paradox as a violation of the sure-thing principle." }, { "id": "ethics-and-game-theory/fair-division-cake-cutting", "title": "Fair Division and Cake-Cutting Algorithms", "url": "tutorials/ethics-and-game-theory/fair-division-cake-cutting/", "topic": "ethics-and-game-theory", "tags": [ "fair-division", "cake-cutting" ], "labels": [ "fairness", "social-choice" ], "date": "2026-05-08", "year": 2026, "summary": "Implement classic fair division protocols including divide-and-choose, the Selfridge-Conway envy-free procedure for three players, and compare proportional versus envy-free allocations with heterogeneous preferences using simulation in R." }, { "id": "ethics-and-game-theory/organ-donation-mechanism", "title": "Organ donation mechanism design", "url": "tutorials/ethics-and-game-theory/organ-donation-mechanism/", "topic": "ethics-and-game-theory", "tags": [ "mechanism-design", "kidney-exchange", "matching" ], "labels": [ "kidney-exchange", "pairwise-matching", "incentive-compatibility", "allocation" ], "date": "2026-05-08", "year": 2026, "summary": "A game-theoretic analysis of kidney exchange as a mechanism design problem, implementing pairwise exchange algorithms inspired by Roth-Sonmez-Unver, with cycle detection in compatibility graphs, incentive analysis, and welfare comparisons of allocation rules." }, { "id": "ethics-and-game-theory/trolley-problem-as-game", "title": "The Trolley Problem as a game under moral uncertainty", "url": "tutorials/ethics-and-game-theory/trolley-problem-as-game/", "topic": "ethics-and-game-theory", "tags": [ "moral-uncertainty", "trolley-problem", "decision-theory" ], "labels": [ "ethics", "decision-under-uncertainty" ], "date": "2026-05-08", "year": 2026, "summary": "Formalize the Trolley Problem and its variants as decision-theoretic games under moral uncertainty in R, comparing utilitarian, deontological, and contractualist frameworks through expected moral value calculations." }, { "id": "ethics-and-game-theory/trolley-problem-game-theory", "title": "The Trolley Problem Through a Game-Theoretic Lens", "url": "tutorials/ethics-and-game-theory/trolley-problem-game-theory/", "topic": "ethics-and-game-theory", "tags": [ "moral-philosophy", "decision-theory" ], "labels": [ "ethics", "decision-theory" ], "date": "2026-05-08", "year": 2026, "summary": "Formalising moral dilemmas as strategic interactions — modelling utilitarian and deontological ethics as payoff specifications, implementing a moral machine framework, and revealing the strategic structure of ethical choice." }, { "id": "ethics-and-game-theory/voting-paradoxes-strategic", "title": "Voting paradoxes and strategic voting", "url": "tutorials/ethics-and-game-theory/voting-paradoxes-strategic/", "topic": "ethics-and-game-theory", "tags": [ "voting-theory", "social-choice", "mechanism-design" ], "labels": [ "ethics-and-game-theory", "mechanism-design" ], "date": "2026-05-08", "year": 2026, "summary": "Explore the Condorcet paradox, Arrow's impossibility theorem, and the Gibbard-Satterthwaite theorem through R simulations showing how rational voters manipulate elections and why no perfect voting rule exists." }, { "id": "ethics-applications/ai-alignment-principal-agent", "title": "AI Alignment as a Principal-Agent Problem", "url": "tutorials/ethics-applications/ai-alignment-principal-agent/", "topic": "ethics-applications", "tags": [ "ai-alignment", "principal-agent" ], "labels": [ "ai-ethics", "mechanism-design" ], "date": "2026-05-08", "year": 2026, "summary": "Model the AI alignment challenge as a principal-agent game with moral hazard, implementing optimal contract design under limited liability and participation constraints, and analysing how increasing agent capability affects the principal's ability to maintain alignment in R." }, { "id": "ethics-applications/algorithmic-fairness-game-theory", "title": "Algorithmic fairness through the lens of game theory", "url": "tutorials/ethics-applications/algorithmic-fairness-game-theory/", "topic": "ethics-applications", "tags": [ "algorithmic-fairness", "mechanism-design" ], "labels": [ "ethics", "fairness", "mechanism-design" ], "date": "2026-05-08", "year": 2026, "summary": "Model fairness constraints in algorithmic decision-making as game-theoretic mechanisms. Compare group fairness, individual fairness, and minimax fairness using R implementations and visualise the trade-offs between accuracy and equity across demographic groups.\n" }, { "id": "ethics-applications/algorithmic-fairness-game", "title": "Algorithmic Fairness as a Multi-Stakeholder Game", "url": "tutorials/ethics-applications/algorithmic-fairness-game/", "topic": "ethics-applications", "tags": [ "algorithmic-fairness", "multi-stakeholder-games" ], "labels": [ "ethics", "fairness" ], "date": "2026-05-08", "year": 2026, "summary": "Modelling the tension between accuracy, fairness, and regulation as a strategic interaction — implementing fairness criteria, demonstrating impossibility results, and computing Pareto frontiers of accuracy vs fairness." }, { "id": "ethics-applications/privacy-game-theory", "title": "Privacy as a game --- strategic information disclosure", "url": "tutorials/ethics-applications/privacy-game-theory/", "topic": "ethics-applications", "tags": [ "privacy", "mechanism-design", "regulation" ], "labels": [ "ethics", "applications" ], "date": "2026-05-08", "year": 2026, "summary": "Model privacy decisions as games between users and data collectors, analyse the privacy paradox, simulate equilibrium disclosure under different regulation regimes, and explore mechanism design for truthful privacy-preference elicitation." }, { "id": "ethics-applications/surveillance-privacy-equilibrium", "title": "Surveillance and privacy as a strategic equilibrium", "url": "tutorials/ethics-applications/surveillance-privacy-equilibrium/", "topic": "ethics-applications", "tags": [ "inspection-games", "privacy", "surveillance" ], "labels": [ "inspection-game", "privacy", "welfare-analysis", "mixed-strategy" ], "date": "2026-05-08", "year": 2026, "summary": "A game-theoretic analysis of the surveillance-privacy tension modeled as an inspection game between a monitoring authority and citizens, with equilibrium computation, welfare analysis, and interactive visualizations of deterrence thresholds." }, { "id": "evolutionary-gt/evolutionarily-stable-strategies", "title": "Evolutionarily stable strategies (ESS)", "url": "tutorials/evolutionary-gt/evolutionarily-stable-strategies/", "topic": "evolutionary-gt", "tags": [ "evolutionarily-stable-strategies", "hawk-dove", "stag-hunt" ], "labels": [ "evolutionary-dynamics", "stability-concepts" ], "date": "2026-05-08", "year": 2026, "summary": "Define and compute evolutionarily stable strategies for symmetric 2x2 games, apply to Hawk-Dove, Stag Hunt, and Prisoner's Dilemma, and visualize invasion dynamics and fitness landscapes." }, { "id": "evolutionary-gt/hawk-dove-war-of-attrition", "title": "Hawk-Dove and the war of attrition — escalation in evolutionary games", "url": "tutorials/evolutionary-gt/hawk-dove-war-of-attrition/", "topic": "evolutionary-gt", "tags": [ "hawk-dove", "war-of-attrition", "escalation" ], "labels": [ "evolutionary-dynamics", "conflict-models" ], "date": "2026-05-08", "year": 2026, "summary": "Model the continuous-time war of attrition as an extension of the Hawk-Dove game in R, derive the mixed ESS with exponential waiting times, and visualise how resource value and fighting costs shape escalation behaviour." }, { "id": "evolutionary-gt/moran-process-finite-populations", "title": "Moran process in finite populations", "url": "tutorials/evolutionary-gt/moran-process-finite-populations/", "topic": "evolutionary-gt", "tags": [ "moran-process", "finite-populations", "stochastic-dynamics" ], "labels": [ "stochastic-dynamics", "finite-populations" ], "date": "2026-05-08", "year": 2026, "summary": "Implement and analyze the Moran process for frequency-dependent selection in finite populations, computing fixation probabilities analytically and via simulation for 2-strategy evolutionary games." }, { "id": "evolutionary-gt/replicator-dynamics-rps", "title": "Replicator dynamics for Rock-Paper-Scissors with deSolve", "url": "tutorials/evolutionary-gt/replicator-dynamics-rps/", "topic": "evolutionary-gt", "tags": [ "replicator-dynamics", "rock-paper-scissors", "desolve" ], "labels": [ "evolutionary-dynamics", "cyclic-games" ], "date": "2026-05-08", "year": 2026, "summary": "Derive and simulate the replicator dynamics for the Rock-Paper-Scissors game in R using deSolve, visualizing cyclic orbits on the 2-simplex." }, { "id": "evolutionary-gt/replicator-mutator-dynamics", "title": "Replicator-mutator dynamics — evolution with mutation", "url": "tutorials/evolutionary-gt/replicator-mutator-dynamics/", "topic": "evolutionary-gt", "tags": [ "replicator-mutator", "mutation", "rock-paper-scissors" ], "labels": [ "evolutionary-dynamics", "mutation" ], "date": "2026-05-08", "year": 2026, "summary": "Extend the standard replicator equation with a mutation matrix Q, implement the ODE system using deSolve in R, and show how mutation stabilises the interior equilibrium of Rock-Paper-Scissors." }, { "id": "evolutionary-gt/spatial-evolutionary-games", "title": "Spatial Evolutionary Games: Cooperation on Grids and Networks", "url": "tutorials/evolutionary-gt/spatial-evolutionary-games/", "topic": "evolutionary-gt", "tags": [ "spatial-games" ], "labels": [ "evolutionary-gt", "spatial-dynamics" ], "date": "2026-05-08", "year": 2026, "summary": "Implement evolutionary dynamics on a 2D lattice where agents play the Prisoner's Dilemma with neighbours, showing how spatial structure enables cooperator clusters to survive even when defection dominates in well-mixed populations." }, { "id": "experimental-economics/beauty-contest-guessing", "title": "The p-beauty contest: level-k thinking and iterated dominance", "url": "tutorials/experimental-economics/beauty-contest-guessing/", "topic": "experimental-economics", "tags": [ "bounded-rationality", "level-k-thinking" ], "labels": [ "experimental", "behavioral" ], "date": "2026-05-08", "year": 2026, "summary": "Simulate the p-beauty contest guessing game to explore bounded rationality, level-k thinking, and the gap between Nash equilibrium predictions and experimental behaviour." }, { "id": "experimental-economics/dictator-game-altruism", "title": "Dictator game and pure altruism", "url": "tutorials/experimental-economics/dictator-game-altruism/", "topic": "experimental-economics", "tags": [ "dictator-game", "altruism", "other-regarding-preferences" ], "labels": [ "experimental-economics", "prosocial-behaviour" ], "date": "2026-05-08", "year": 2026, "summary": "The dictator game as a test of pure altruism versus strategic motives, with warm-glow and CES utility models calibrated to Engel's (2011) meta-analysis of experimental giving distributions." }, { "id": "experimental-economics/public-goods-experiment", "title": "The public goods game — free-riding in the laboratory", "url": "tutorials/experimental-economics/public-goods-experiment/", "topic": "experimental-economics", "tags": [ "public-goods", "free-riding" ], "labels": [ "experimental-design", "social-dilemmas" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the linear public goods game in R, analyse experimental data patterns including the decay of cooperation over rounds, and model how punishment mechanisms sustain contributions." }, { "id": "experimental-economics/trust-game-reciprocity", "title": "Trust game and reciprocity", "url": "tutorials/experimental-economics/trust-game-reciprocity/", "topic": "experimental-economics", "tags": [ "trust-game", "reciprocity", "backward-induction" ], "labels": [ "experimental-economics", "reciprocity" ], "date": "2026-05-08", "year": 2026, "summary": "The Berg, Dickhaut & McCabe (1995) trust game as a test of trust and reciprocity: backward induction predicts zero investment, yet experimental evidence shows substantial trust and conditional reciprocity, modelled here with heterogeneous reciprocity preferences." }, { "id": "experimental-economics/voluntary-contribution-mechanism", "title": "The Voluntary Contribution Mechanism for Public Goods", "url": "tutorials/experimental-economics/voluntary-contribution-mechanism/", "topic": "experimental-economics", "tags": [ "public-goods", "free-riding" ], "labels": [ "experimental-economics", "public-goods" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the classic linear public goods game in R, simulating declining contributions, the restart effect, and the impact of the marginal per-capita return on free-riding behaviour, with comparison to punishment mechanisms." }, { "id": "foundations/backward-induction-centipede", "title": "Backward induction and the centipede game paradox", "url": "tutorials/foundations/backward-induction-centipede/", "topic": "foundations", "tags": [ "backward-induction", "centipede-game", "paradox" ], "labels": [ "equilibrium-concepts", "rationality" ], "date": "2026-05-08", "year": 2026, "summary": "Implement backward induction for the centipede game in R, demonstrate the dramatic gap between theory and observed play, and analyse how finite vs infinite horizons shape rational behaviour." }, { "id": "foundations/common-knowledge-paradoxes", "title": "Common knowledge and its paradoxes", "url": "tutorials/foundations/common-knowledge-paradoxes/", "topic": "foundations", "tags": [ "common-knowledge", "epistemic-game-theory", "paradoxes" ], "labels": [ "equilibrium-concepts", "epistemic-gt" ], "date": "2026-05-08", "year": 2026, "summary": "Formalise common knowledge using Aumann's partition model in R, implement the muddy children puzzle to show how public announcements create common knowledge, and analyse how failures of common knowledge lead to coordination failures, speculative trade, and the electronic mail game paradox." }, { "id": "foundations/correlated-equilibrium", "title": "Correlated equilibrium — coordination through shared signals", "url": "tutorials/foundations/correlated-equilibrium/", "topic": "foundations", "tags": [ "correlated-equilibrium", "equilibrium-concepts", "coordination" ], "labels": [ "equilibrium-concepts", "coordination" ], "date": "2026-05-08", "year": 2026, "summary": "Implement Aumann's correlated equilibrium in R via linear programming, compare it with Nash equilibrium, and visualize how a public correlating device expands the set of achievable payoffs." }, { "id": "foundations/dominant-strategies-iterated-elimination", "title": "Dominant strategies and iterated elimination of dominated strategies", "url": "tutorials/foundations/dominant-strategies-iterated-elimination/", "topic": "foundations", "tags": [ "dominance", "rationality", "normal-form" ], "labels": [ "equilibrium-concepts", "solution-concepts" ], "date": "2026-05-08", "year": 2026, "summary": "Define strict and weak dominance in normal-form games, implement iterated elimination of dominated strategies (IEDS) in R, and show how rationality assumptions progressively simplify strategic analysis." }, { "id": "foundations/epsilon-equilibrium-approximate", "title": "Epsilon-equilibrium and approximate Nash equilibria", "url": "tutorials/foundations/epsilon-equilibrium-approximate/", "topic": "foundations", "tags": [ "epsilon-equilibrium", "approximate-equilibrium", "computational-complexity" ], "labels": [ "equilibrium-concepts", "computational-gt" ], "date": "2026-05-08", "year": 2026, "summary": "Implement epsilon-Nash equilibrium in R, analyse when approximate solutions suffice for practical predictions, compute the epsilon required for various games, and connect to computational complexity of exact Nash equilibrium finding." }, { "id": "foundations/extensive-form-subgame-perfection", "title": "Extensive-form games and subgame-perfect equilibrium", "url": "tutorials/foundations/extensive-form-subgame-perfection/", "topic": "foundations", "tags": [ "extensive-form", "subgame-perfection", "backward-induction" ], "labels": [ "equilibrium-concepts", "sequential-games" ], "date": "2026-05-08", "year": 2026, "summary": "Formalize sequential games as extensive-form game trees in R, implement backward induction to find subgame-perfect equilibria, and visualize the difference between Nash equilibria and credible equilibria." }, { "id": "foundations/folk-theorem-perfect-monitoring", "title": "Folk theorem with perfect monitoring", "url": "tutorials/foundations/folk-theorem-perfect-monitoring/", "topic": "foundations", "tags": [ "repeated-games", "folk-theorem", "subgame-perfection" ], "labels": [ "repeated-games", "equilibrium-refinements" ], "date": "2026-05-08", "year": 2026, "summary": "Prove and visualize the folk theorem for infinitely repeated games: any individually rational, feasible payoff can be sustained as a subgame-perfect equilibrium when players are sufficiently patient." }, { "id": "foundations/nash-bargaining-solution", "title": "The Nash bargaining solution", "url": "tutorials/foundations/nash-bargaining-solution/", "topic": "foundations", "tags": [ "bargaining", "nash-bargaining", "cooperative-gt" ], "labels": [ "equilibrium-concepts", "cooperative-gt" ], "date": "2026-05-08", "year": 2026, "summary": "Derive and implement Nash's axiomatic bargaining solution in R, compute the Nash product for two-player bargaining problems, and visualize the Pareto frontier with the bargaining outcome." }, { "id": "foundations/nash-equilibrium-mixed", "title": "Mixed-strategy Nash equilibrium in 2×2 games", "url": "tutorials/foundations/nash-equilibrium-mixed/", "topic": "foundations", "tags": [ "nash-equilibrium", "mixed-strategies", "2x2-games" ], "labels": [ "normal-form", "solution-concepts" ], "date": "2026-05-08", "year": 2026, "summary": "How to compute a mixed-strategy Nash equilibrium for a 2×2 normal-form game, with R and Python implementations and interactive visualizations." }, { "id": "foundations/rationalizability", "title": "Rationalizability and iterated dominance — the epistemic foundation of game theory", "url": "tutorials/foundations/rationalizability/", "topic": "foundations", "tags": [ "rationalizability", "dominance", "epistemic-game-theory" ], "labels": [ "equilibrium-concepts", "solution-concepts" ], "date": "2026-05-08", "year": 2026, "summary": "Define rationalizable strategies as those surviving iterated deletion of never-best-responses, implement the algorithm in R for arbitrary games, and show the relationship to IESDS and common knowledge of rationality." }, { "id": "foundations/revelation-principle", "title": "The revelation principle — why truth-telling mechanisms suffice", "url": "tutorials/foundations/revelation-principle/", "topic": "foundations", "tags": [ "revelation-principle", "mechanism-design", "incentive-compatibility" ], "labels": [ "mechanism-design", "equilibrium-concepts" ], "date": "2026-05-08", "year": 2026, "summary": "Prove and implement the revelation principle in R, showing that any outcome achievable by any mechanism can be replicated by a direct mechanism where truthful reporting is optimal, with applications to auctions and public goods provision." }, { "id": "foundations/signaling-games-pbe", "title": "Signaling games and perfect Bayesian equilibrium", "url": "tutorials/foundations/signaling-games-pbe/", "topic": "foundations", "tags": [ "signaling-games", "perfect-bayesian-equilibrium", "incomplete-information" ], "labels": [ "equilibrium-concepts", "incomplete-information" ], "date": "2026-05-08", "year": 2026, "summary": "Model strategic communication under asymmetric information in R, compute perfect Bayesian equilibria with separating and pooling strategies, and visualize how informed players signal their types." }, { "id": "foundations/trembling-hand-refinement", "title": "Trembling Hand Perfect Equilibrium", "url": "tutorials/foundations/trembling-hand-refinement/", "topic": "foundations", "tags": [ "equilibrium-refinement", "trembling-hand-perfection", "nash-equilibrium" ], "labels": [ "foundations", "refinements" ], "date": "2026-05-08", "year": 2026, "summary": "Implement Selten's trembling hand perfection refinement to eliminate unreasonable Nash equilibria by requiring robustness to small probability mistakes, with applications to coordination games and weakly dominated strategies." }, { "id": "foundations/zero-sum-minimax-theorem", "title": "Zero-sum games and the minimax theorem", "url": "tutorials/foundations/zero-sum-minimax-theorem/", "topic": "foundations", "tags": [ "zero-sum", "minimax", "linear-programming" ], "labels": [ "equilibrium-concepts", "classical-results" ], "date": "2026-05-08", "year": 2026, "summary": "Prove and implement von Neumann's minimax theorem for two-player zero-sum games in R, compute minimax strategies via linear programming, and visualize the security level geometry." }, { "id": "history-of-gt-mathematics/nash-equilibrium-original-proof", "title": "Nash's existence proof — historical context and intuition", "url": "tutorials/history-of-gt-mathematics/nash-equilibrium-original-proof/", "topic": "history-of-gt-mathematics", "tags": [ "nash-equilibrium", "fixed-point-theorems", "existence-proofs" ], "labels": [ "history-of-gt-mathematics", "foundations" ], "date": "2026-05-08", "year": 2026, "summary": "A historical and mathematical account of John Nash's 1950 proof that every finite game has a mixed-strategy equilibrium, with visual demonstrations of best-response correspondences, fixed points, and connections to computational complexity." }, { "id": "history-of-gt-mathematics/selten-trembling-hand-perfection", "title": "Selten's trembling hand perfection --- historical and technical", "url": "tutorials/history-of-gt-mathematics/selten-trembling-hand-perfection/", "topic": "history-of-gt-mathematics", "tags": [ "equilibrium-refinements", "trembling-hand-perfection", "nash-equilibrium" ], "labels": [ "history-of-gt-mathematics", "foundations" ], "date": "2026-05-08", "year": 2026, "summary": "A historical and mathematical account of Reinhard Selten's 1975 trembling hand perfect equilibrium refinement, with R implementations that verify perfection by constructing sequences of completely mixed strategy profiles converging to candidate equilibria." }, { "id": "history-of-gt-mathematics/von-neumann-minimax-proof", "title": "Von Neumann's minimax theorem: proof and implementation", "url": "tutorials/history-of-gt-mathematics/von-neumann-minimax-proof/", "topic": "history-of-gt-mathematics", "tags": [ "minimax-theorem", "zero-sum-games", "linear-programming" ], "labels": [ "minimax", "zero-sum", "lp-duality", "saddle-point" ], "date": "2026-05-08", "year": 2026, "summary": "A rigorous treatment of von Neumann's 1928 minimax theorem for two-person zero-sum games, including a constructive proof via linear programming duality, a full R implementation using lpSolve, and interactive visualizations of the minimax solution surface." }, { "id": "history-of-gt-mathematics/von-neumann-to-nash-timeline", "title": "From von Neumann to Nash — a mathematical timeline of game theory", "url": "tutorials/history-of-gt-mathematics/von-neumann-to-nash-timeline/", "topic": "history-of-gt-mathematics", "tags": [ "timeline", "mathematical-history" ], "labels": [ "history", "foundations" ], "date": "2026-05-08", "year": 2026, "summary": "Interactive timeline of key results from the 1928 minimax theorem through Nash's 1950-51 equilibrium existence proof, with R visualizations of each milestone's mathematical contribution to game theory." }, { "id": "history-of-gt-mathematics/zermelo-chess-theorem", "title": "Zermelo's Theorem -- The First Formal Result in Game Theory", "url": "tutorials/history-of-gt-mathematics/zermelo-chess-theorem/", "topic": "history-of-gt-mathematics", "tags": [ "backward-induction", "combinatorial-games" ], "labels": [ "history-of-gt", "combinatorial-games" ], "date": "2026-05-08", "year": 2026, "summary": "Explore Zermelo's 1913 theorem on determined games, implementing backward induction for Nim and simplified chess endgames in R, with Sprague-Grundy theory and Grundy value computation." }, { "id": "information-theory/cheap-talk-communication", "title": "Cheap talk and strategic communication", "url": "tutorials/information-theory/cheap-talk-communication/", "topic": "information-theory", "tags": [ "cheap-talk", "strategic-communication", "signalling" ], "labels": [ "information-theory", "cheap-talk" ], "date": "2026-05-08", "year": 2026, "summary": "The Crawford-Sobel (1982) cheap talk model: how costless, non-verifiable messages can transmit information when preferences are misaligned, with partition equilibria, information loss as a function of bias, and connections to costly signalling games." }, { "id": "information-theory/entropy-and-strategic-information", "title": "Entropy and the value of information in strategic games", "url": "tutorials/information-theory/entropy-and-strategic-information/", "topic": "information-theory", "tags": [ "entropy", "value-of-information" ], "labels": [ "information-theory", "strategic-uncertainty" ], "date": "2026-05-08", "year": 2026, "summary": "Apply Shannon entropy to game-theoretic information sets, quantify uncertainty reduction, and compare the value of perfect versus imperfect information using R implementations." }, { "id": "information-theory/entropy-correlated-equilibrium", "title": "Maximum Entropy Correlated Equilibria", "url": "tutorials/information-theory/entropy-correlated-equilibrium/", "topic": "information-theory", "tags": [ "correlated-equilibrium", "entropy" ], "labels": [ "information-theory", "equilibrium-concepts" ], "date": "2026-05-08", "year": 2026, "summary": "Compute the maximum entropy correlated equilibrium of a game as a constrained optimisation problem in R, comparing it with welfare-maximising CE and analysing mutual information between signals and actions." }, { "id": "information-theory/rational-inattention", "title": "Rational inattention: information costs and strategic behaviour", "url": "tutorials/information-theory/rational-inattention/", "topic": "information-theory", "tags": [ "rational-inattention", "bounded-rationality" ], "labels": [ "information-theory", "behavioral" ], "date": "2026-05-08", "year": 2026, "summary": "Model agents who face Shannon mutual information costs for acquiring information about the state, showing how limited attention leads to sticky behaviour, stochastic choice, and deviations from full-information equilibrium." }, { "id": "information-theory/value-of-information-games", "title": "Value of information in strategic games", "url": "tutorials/information-theory/value-of-information-games/", "topic": "information-theory", "tags": [ "value-of-information", "decision-theory", "bayesian-games" ], "labels": [ "information-theory", "decision-theory" ], "date": "2026-05-08", "year": 2026, "summary": "Compute the value of perfect and imperfect information in decision problems and games, showing that more information always helps a single agent but can hurt in strategic interaction." }, { "id": "linear-algebra-matrix/eigenvalue-methods-repeated-games", "title": "Eigenvalue methods for repeated game analysis", "url": "tutorials/linear-algebra-matrix/eigenvalue-methods-repeated-games/", "topic": "linear-algebra-matrix", "tags": [ "repeated-games", "markov-chains", "eigenvalue-decomposition" ], "labels": [ "linear-algebra-matrix", "repeated-games" ], "date": "2026-05-08", "year": 2026, "summary": "Use eigenvalue decomposition to compute stationary distributions, convergence rates, and long-run cooperation levels for Markov strategies in the repeated Prisoner's Dilemma, including Tit-for-Tat, Grim Trigger, and stochastic strategies." }, { "id": "linear-algebra-matrix/lp-duality-zero-sum", "title": "LP duality and zero-sum game solutions", "url": "tutorials/linear-algebra-matrix/lp-duality-zero-sum/", "topic": "linear-algebra-matrix", "tags": [ "linear-programming", "zero-sum-games", "minimax" ], "labels": [ "linear-algebra-matrix", "optimization" ], "date": "2026-05-08", "year": 2026, "summary": "Explore the formal connection between linear programming duality and the minimax theorem for zero-sum games, implementing both primal and dual formulations to solve a 3x3 game." }, { "id": "linear-algebra-matrix/markov-chains-strategy-dynamics", "title": "Markov Chains for Strategy Dynamics in Game Theory", "url": "tutorials/linear-algebra-matrix/markov-chains-strategy-dynamics/", "topic": "linear-algebra-matrix", "tags": [ "markov-chains", "evolutionary-dynamics" ], "labels": [ "linear-algebra", "evolutionary-gt" ], "date": "2026-05-08", "year": 2026, "summary": "Model strategy updating as a Markov chain in populations playing 2x2 games, computing transition matrices, stationary distributions, and mixing times for imitation dynamics and mutation-selection processes." }, { "id": "linear-algebra-matrix/matrix-games-and-linear-algebra", "title": "Matrix games — linear algebra foundations for game theory", "url": "tutorials/linear-algebra-matrix/matrix-games-and-linear-algebra/", "topic": "linear-algebra-matrix", "tags": [ "matrix-games", "numerical-methods" ], "labels": [ "linear-algebra", "equilibrium-computation" ], "date": "2026-05-08", "year": 2026, "summary": "Express strategic games as matrices, compute mixed-strategy Nash equilibria using linear algebra operations including eigenvalues, null spaces, and linear programming, and build a foundation for numerical game theory in R." }, { "id": "linear-algebra-matrix/singular-value-decomposition-games", "title": "Singular value decomposition for game analysis", "url": "tutorials/linear-algebra-matrix/singular-value-decomposition-games/", "topic": "linear-algebra-matrix", "tags": [ "svd", "payoff-matrices", "dimensionality-reduction" ], "labels": [ "linear-algebra", "matrix-methods" ], "date": "2026-05-08", "year": 2026, "summary": "Apply SVD to analyze payoff matrices, identify dominant strategic dimensions, construct low-rank game approximations, and connect matrix rank to mixed strategy structure." }, { "id": "mechanism-design/combinatorial-auctions", "title": "Combinatorial Auctions — Bidding on Bundles of Items", "url": "tutorials/mechanism-design/combinatorial-auctions/", "topic": "mechanism-design", "tags": [ "combinatorial-auctions", "integer-programming" ], "labels": [ "auction-theory", "mechanism-design" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the winner determination problem for combinatorial auctions using integer programming with lpSolve, model a spectrum auction with complementarities, compare VCG and first-price payment rules, and demonstrate the exposure problem in R." }, { "id": "mechanism-design/deferred-acceptance", "title": "Deferred acceptance — stable matching via the Gale-Shapley algorithm", "url": "tutorials/mechanism-design/deferred-acceptance/", "topic": "mechanism-design", "tags": [ "stable-matching", "gale-shapley", "market-design" ], "labels": [ "mechanism-design", "matching-theory" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the Gale-Shapley deferred acceptance algorithm for stable matching in R, prove proposer-optimality and strategy-proofness, simulate matching quality across problem sizes, and visualize the lattice of stable matchings." }, { "id": "mechanism-design/matching-markets-practical", "title": "Practical Matching Market Design: From NRMP to School Choice", "url": "tutorials/mechanism-design/matching-markets-practical/", "topic": "mechanism-design", "tags": [ "matching-markets" ], "labels": [ "mechanism-design", "matching" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the Gale-Shapley deferred acceptance algorithm for many-to-one matching, simulate the National Resident Matching Program, and compare with Top Trading Cycles for school choice." }, { "id": "mechanism-design/mechanism-design-intro", "title": "Introduction to mechanism design — engineering incentives in strategic environments", "url": "tutorials/mechanism-design/mechanism-design-intro/", "topic": "mechanism-design", "tags": [ "revelation-principle", "gibbard-satterthwaite", "implementation-theory" ], "labels": [ "mechanism-design", "foundations" ], "date": "2026-05-08", "year": 2026, "summary": "Survey the foundations of mechanism design as 'reverse game theory,' covering the revelation principle, Gibbard-Satterthwaite impossibility, and implementation theory, with a worked R implementation of the pivotal mechanism for public goods provision." }, { "id": "mechanism-design/vcg-mechanism", "title": "The VCG mechanism — optimal multi-item allocation with truthful bidding", "url": "tutorials/mechanism-design/vcg-mechanism/", "topic": "mechanism-design", "tags": [ "vcg", "combinatorial-auctions", "incentive-compatibility" ], "labels": [ "mechanism-design", "auction-theory" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the Vickrey-Clarke-Groves mechanism for combinatorial allocation in R, prove dominant-strategy incentive compatibility and allocative efficiency, compute Clarke pivot payments, and compare to sequential auctions." }, { "id": "mechanism-design/vickrey-second-price-auction", "title": "The Vickrey (second-price) auction — truth-telling as a dominant strategy", "url": "tutorials/mechanism-design/vickrey-second-price-auction/", "topic": "mechanism-design", "tags": [ "auctions", "vickrey", "dominant-strategy" ], "labels": [ "mechanism-design", "auction-theory" ], "date": "2026-05-08", "year": 2026, "summary": "Analyse the Vickrey sealed-bid second-price auction in R, prove that truthful bidding is a weakly dominant strategy, simulate revenue comparisons with first-price auctions, and visualize bidding equilibria." }, { "id": "ml-and-gt/adversarial-robustness-games", "title": "Adversarial robustness as a game", "url": "tutorials/ml-and-gt/adversarial-robustness-games/", "topic": "ml-and-gt", "tags": [ "adversarial-robustness", "minimax", "classification" ], "labels": [ "ml-and-gt", "adversarial-robustness" ], "date": "2026-05-08", "year": 2026, "summary": "Adversarial machine learning formulated as a two-player zero-sum game between a Defender (classifier) and an Attacker who perturbs inputs: minimax optimisation, adversarial training, and the effect on decision boundaries demonstrated with a 2D classification task." }, { "id": "ml-and-gt/deep-reinforcement-learning-games", "title": "Deep reinforcement learning for strategic games", "url": "tutorials/ml-and-gt/deep-reinforcement-learning-games/", "topic": "ml-and-gt", "tags": [ "reinforcement-learning", "neural-networks", "self-play" ], "labels": [ "machine-learning", "reinforcement-learning" ], "date": "2026-05-08", "year": 2026, "summary": "Implement simple deep RL agents from scratch in R that learn game strategies through self-play, comparing learned policies with analytical Nash equilibria." }, { "id": "ml-and-gt/fictitious-play-convergence", "title": "Fictitious play and convergence", "url": "tutorials/ml-and-gt/fictitious-play-convergence/", "topic": "ml-and-gt", "tags": [ "fictitious-play", "learning-in-games", "nash-equilibrium" ], "labels": [ "ml-and-gt", "learning-in-games" ], "date": "2026-05-08", "year": 2026, "summary": "Implement Brown's fictitious play algorithm for 2x2 and 3x3 games, demonstrating convergence in zero-sum and potential games and the classic non-convergence cycling in Shapley's counterexample." }, { "id": "ml-and-gt/multi-agent-reinforcement-learning", "title": "Multi-agent reinforcement learning in matrix games", "url": "tutorials/ml-and-gt/multi-agent-reinforcement-learning/", "topic": "ml-and-gt", "tags": [ "reinforcement-learning", "multi-agent" ], "labels": [ "machine-learning", "multi-agent-systems" ], "date": "2026-05-08", "year": 2026, "summary": "Implement independent Q-learning agents that learn to play 2x2 matrix games, analyse convergence behaviour across game classes, and investigate when learning dynamics converge (or fail to converge) to Nash equilibria." }, { "id": "ml-and-gt/no-regret-learning-games", "title": "No-regret learning in games: from multiplicative weights to equilibrium", "url": "tutorials/ml-and-gt/no-regret-learning-games/", "topic": "ml-and-gt", "tags": [ "no-regret-learning", "online-learning" ], "labels": [ "machine-learning", "online-learning" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the Multiplicative Weights Update algorithm and show that when all players use no-regret learning, the time-averaged strategy profile converges to a coarse correlated equilibrium." }, { "id": "network-games/braess-paradox-routing", "title": "Braess's paradox — when adding roads makes traffic worse", "url": "tutorials/network-games/braess-paradox-routing/", "topic": "network-games", "tags": [ "braess-paradox", "routing-games", "price-of-anarchy" ], "labels": [ "network-games", "inefficiency" ], "date": "2026-05-08", "year": 2026, "summary": "Implement Braess's paradox in R, compute Wardrop equilibrium flows on networks with selfish routing, demonstrate how adding capacity can increase total latency, and compare the price of anarchy across network topologies." }, { "id": "network-games/congestion-games-potential", "title": "Congestion games and potential functions", "url": "tutorials/network-games/congestion-games-potential/", "topic": "network-games", "tags": [ "congestion-games", "potential-games", "braess-paradox" ], "labels": [ "network-games", "potential-games" ], "date": "2026-05-08", "year": 2026, "summary": "Implement Rosenthal's congestion games with Monderer-Shapley potential functions, demonstrate the existence of pure Nash equilibria, and visualise Braess's paradox in a traffic network." }, { "id": "network-games/network-formation-strategic", "title": "Strategic network formation — who links with whom?", "url": "tutorials/network-games/network-formation-strategic/", "topic": "network-games", "tags": [ "network-formation", "pairwise-stability" ], "labels": [ "network-games", "strategic-formation" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the Jackson-Wolinsky connections model in R, analyse pairwise stability and efficiency of network structures, and visualise the tension between stable and efficient networks using igraph." }, { "id": "network-games/public-goods-on-networks", "title": "Public goods provision on networks", "url": "tutorials/network-games/public-goods-on-networks/", "topic": "network-games", "tags": [ "public-goods", "network-topology", "free-riding" ], "labels": [ "network-games", "public-goods" ], "date": "2026-05-08", "year": 2026, "summary": "Public goods games played on networks where contributions benefit neighbours: how network topology --- star, circle, and random graphs --- shapes equilibrium provision, free-riding by central agents, and aggregate welfare through best-response dynamics on adjacency matrices." }, { "id": "network-games/two-sided-markets-platforms", "title": "Two-sided markets and platform competition", "url": "tutorials/network-games/two-sided-markets-platforms/", "topic": "network-games", "tags": [ "two-sided-markets", "platform-economics", "network-externalities" ], "labels": [ "network-economics", "industrial-organization" ], "date": "2026-05-08", "year": 2026, "summary": "Model platform markets as two-sided network games with cross-side externalities, analyzing pricing structure, platform competition, tipping, and multihoming." }, { "id": "network-science/centrality-measures-game-theory", "title": "Centrality measures for game-theoretic network analysis", "url": "tutorials/network-science/centrality-measures-game-theory/", "topic": "network-science", "tags": [ "centrality", "graph-theory" ], "labels": [ "network-science", "centrality-analysis" ], "date": "2026-05-08", "year": 2026, "summary": "Compute degree, betweenness, and eigenvector centrality for strategic networks using igraph in R, and visualise how different centrality measures reveal distinct power structures in game-theoretic settings." }, { "id": "network-science/community-detection-coalitions", "title": "Community Detection as Coalition Formation", "url": "tutorials/network-science/community-detection-coalitions/", "topic": "network-science", "tags": [ "community-detection", "coalition-formation" ], "labels": [ "cooperative-gt", "networks" ], "date": "2026-05-08", "year": 2026, "summary": "Discovering network communities through the lens of cooperative game theory — modelling dense subgroups as coalitions, implementing modularity-based detection, and analysing Nash stability of the resulting partitions." }, { "id": "network-science/diffusion-cascades-networks", "title": "Diffusion and cascades on networks", "url": "tutorials/network-science/diffusion-cascades-networks/", "topic": "network-science", "tags": [ "cascades", "diffusion", "coordination-games" ], "labels": [ "network-science", "diffusion" ], "date": "2026-05-08", "year": 2026, "summary": "Simulate information cascades using the linear threshold and independent cascade models on random networks, demonstrating tipping points and the effect of network structure on cascade size." }, { "id": "network-science/power-law-networks-strategic", "title": "Power-law networks and strategic behaviour", "url": "tutorials/network-science/power-law-networks-strategic/", "topic": "network-science", "tags": [ "scale-free-networks", "coordination-games", "network-interventions" ], "labels": [ "network-science", "simulations" ], "date": "2026-05-08", "year": 2026, "summary": "Analyse how scale-free degree distributions in Barabasi-Albert networks affect coordination game outcomes, hub influence on equilibrium selection, and targeted vs random intervention strategies using R simulations." }, { "id": "network-science/strategic-network-interdiction", "title": "Strategic network interdiction: max-flow, min-cut, and Stackelberg games", "url": "tutorials/network-science/strategic-network-interdiction/", "topic": "network-science", "tags": [ "network-interdiction", "zero-sum-games" ], "labels": [ "networks", "optimization" ], "date": "2026-05-08", "year": 2026, "summary": "Model network interdiction as a two-player zero-sum game where an attacker removes edges to minimise maximum flow while a defender protects critical links. Explore the resilience-efficiency trade-off." }, { "id": "optimization-numerical-methods/gradient-descent-nash-finding", "title": "Gradient Descent Methods for Finding Nash Equilibria", "url": "tutorials/optimization-numerical-methods/gradient-descent-nash-finding/", "topic": "optimization-numerical-methods", "tags": [ "gradient-descent", "nash-equilibrium" ], "labels": [ "numerical-methods", "continuous-games" ], "date": "2026-05-08", "year": 2026, "summary": "Implement gradient-based optimisation algorithms for finding Nash equilibria in continuous games, including best-response dynamics, the Nikaido-Isoda function approach, and simultaneous gradient descent with convergence analysis in R." }, { "id": "optimization-numerical-methods/interior-point-game-solving", "title": "Interior Point Methods for Solving Game-Theoretic Optimization Problems", "url": "tutorials/optimization-numerical-methods/interior-point-game-solving/", "topic": "optimization-numerical-methods", "tags": [ "interior-point-methods", "zero-sum-games", "linear-programming" ], "labels": [ "optimization", "numerical" ], "date": "2026-05-08", "year": 2026, "summary": "Implement barrier methods for the linear programming formulation of zero-sum games, visualise the central path and barrier parameter convergence, and apply log-barrier techniques to compute correlated equilibria." }, { "id": "optimization-numerical-methods/lemke-howson-algorithm", "title": "The Lemke-Howson algorithm for computing Nash equilibria", "url": "tutorials/optimization-numerical-methods/lemke-howson-algorithm/", "topic": "optimization-numerical-methods", "tags": [ "lemke-howson", "equilibrium-computation" ], "labels": [ "algorithms", "equilibrium-computation" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the Lemke-Howson pivoting algorithm for bimatrix games in R, trace the complementary path from an artificial equilibrium to a Nash equilibrium, and visualise the pivot steps on the best-response polytope." }, { "id": "optimization-numerical-methods/simulated-annealing-equilibria", "title": "Simulated annealing for equilibrium computation", "url": "tutorials/optimization-numerical-methods/simulated-annealing-equilibria/", "topic": "optimization-numerical-methods", "tags": [ "simulated-annealing", "nash-equilibrium", "metaheuristic" ], "labels": [ "optimization", "numerical-methods" ], "date": "2026-05-08", "year": 2026, "summary": "Apply simulated annealing to find Nash equilibria in complex games, comparing temperature schedules and neighborhood structures with gradient-based methods." }, { "id": "optimization-numerical-methods/support-enumeration-algorithm", "title": "Support enumeration algorithm for Nash equilibria", "url": "tutorials/optimization-numerical-methods/support-enumeration-algorithm/", "topic": "optimization-numerical-methods", "tags": [ "nash-equilibrium", "support-enumeration", "bimatrix-games" ], "labels": [ "optimization-numerical-methods", "nash-equilibrium" ], "date": "2026-05-08", "year": 2026, "summary": "Implement the support enumeration method to find all Nash equilibria of bimatrix games by solving indifference conditions for each support pair, with applications to games with multiple equilibria." }, { "id": "public-apis-and-datasets/federal-reserve-fred-data", "title": "FRED economic data for game-theoretic calibration", "url": "tutorials/public-apis-and-datasets/federal-reserve-fred-data/", "topic": "public-apis-and-datasets", "tags": [ "fred", "cournot-competition", "demand-estimation" ], "labels": [ "data-access", "calibration" ], "date": "2026-05-08", "year": 2026, "summary": "Access Federal Reserve FRED data via the fredr API or direct CSV download to calibrate game-theoretic models with real-world economic parameters such as interest rates, GDP growth, and manufacturing output." }, { "id": "public-apis-and-datasets/kaggle-competition-strategic", "title": "Kaggle competitions as strategic interactions", "url": "tutorials/public-apis-and-datasets/kaggle-competition-strategic/", "topic": "public-apis-and-datasets", "tags": [ "kaggle", "nash-equilibrium", "strategic-interaction" ], "labels": [ "applied-gt", "competition" ], "date": "2026-05-08", "year": 2026, "summary": "Analyze Kaggle competitions through a game-theoretic lens, modeling competitor strategies, Nash equilibria of submission timing, and strategic model selection under competition rules." }, { "id": "public-apis-and-datasets/openai-gym-game-environments", "title": "Game Theory Environments for Reinforcement Learning in R", "url": "tutorials/public-apis-and-datasets/openai-gym-game-environments/", "topic": "public-apis-and-datasets", "tags": [ "reinforcement-learning", "game-environments" ], "labels": [ "machine-learning", "simulation" ], "date": "2026-05-08", "year": 2026, "summary": "Build OpenAI Gym-inspired game theory environments in pure R using R6 classes with reset(), step(), and render() methods. Implement Q-learning agents that learn Nash equilibrium strategies in Prisoner's Dilemma and Hawk-Dove games." }, { "id": "public-apis-and-datasets/world-bank-development-games", "title": "Development Economics as Game Theory with World Bank Data", "url": "tutorials/public-apis-and-datasets/world-bank-development-games/", "topic": "public-apis-and-datasets", "tags": [ "development-economics", "international-relations" ], "labels": [ "applications", "public-data" ], "date": "2026-05-08", "year": 2026, "summary": "Modelling international development as strategic interaction — aid allocation auctions, trade as repeated prisoner's dilemma, and technology transfer as signalling games, using simulated indicators inspired by World Bank data." }, { "id": "public-apis-and-datasets/world-bank-wdi-economic-indicators", "title": "World Bank WDI — economic indicators for game-theoretic analysis", "url": "tutorials/public-apis-and-datasets/world-bank-wdi-economic-indicators/", "topic": "public-apis-and-datasets", "tags": [ "world-bank", "wdi", "international-economics" ], "labels": [ "data-sources", "international-economics" ], "date": "2026-05-08", "year": 2026, "summary": "Access the World Bank's World Development Indicators via the WDI R package, explore GDP, trade openness, and military expenditure data relevant to international game-theoretic models." }, { "id": "r-package-development/building-game-theory-r-package", "title": "Building a game theory R package from scratch", "url": "tutorials/r-package-development/building-game-theory-r-package/", "topic": "r-package-development", "tags": [ "devtools", "testthat" ], "labels": [ "r-package", "software-engineering", "nash-equilibrium" ], "date": "2026-05-08", "year": 2026, "summary": "Walk through every step of creating a minimal R package that includes a nash_2x2() solver for 2x2 normal-form games, complete with roxygen2 documentation, testthat unit tests, and a devtools-powered workflow.\n" }, { "id": "r-package-development/rcpp-game-solvers", "title": "Accelerating Game Solvers with Rcpp and Optimised R", "url": "tutorials/r-package-development/rcpp-game-solvers/", "topic": "r-package-development", "tags": [ "performance-optimisation", "rcpp" ], "labels": [ "r-development", "performance" ], "date": "2026-05-08", "year": 2026, "summary": "Profiling game-theoretic computations in R, implementing support enumeration and fictitious play, presenting Rcpp C++ code for acceleration, and benchmarking pure-R optimisation strategies for performance-critical solvers." }, { "id": "r-package-development/s4-classes-game-objects", "title": "Designing S4 Classes for Game Theory Objects in R", "url": "tutorials/r-package-development/s4-classes-game-objects/", "topic": "r-package-development", "tags": [ "s4-classes", "object-oriented-design" ], "labels": [ "r-development", "oop" ], "date": "2026-05-08", "year": 2026, "summary": "Build a formal S4 class hierarchy for game theory in R with NormalFormGame, Strategy, and Equilibrium classes, including validity checks, show/summary methods, and Nash equilibrium solving via support enumeration." }, { "id": "r-package-development/testing-game-theory-code", "title": "Testing game theory code with testthat", "url": "tutorials/r-package-development/testing-game-theory-code/", "topic": "r-package-development", "tags": [ "testing", "testthat", "nash-equilibrium" ], "labels": [ "testing", "software-engineering" ], "date": "2026-05-08", "year": 2026, "summary": "Best practices for testing game-theoretic computations using testthat, including property-based testing of Nash equilibria, dominance checking, payoff validation, and test-driven development for game solvers." }, { "id": "r-package-development/vignette-writing-game-packages", "title": "Writing vignettes for game theory R packages", "url": "tutorials/r-package-development/vignette-writing-game-packages/", "topic": "r-package-development", "tags": [ "vignettes", "cran", "documentation" ], "labels": [ "software-engineering", "documentation" ], "date": "2026-05-08", "year": 2026, "summary": "Best practices for creating package vignettes that demonstrate game-theoretic computations, from structure and examples to testing and CRAN submission." }, { "id": "real-world-data-applications/arms-race-cold-war", "title": "The arms race as iterated Prisoner's Dilemma — a Cold War analysis", "url": "tutorials/real-world-data-applications/arms-race-cold-war/", "topic": "real-world-data-applications", "tags": [ "arms-race", "prisoners-dilemma", "cold-war" ], "labels": [ "applied-game-theory", "historical-applications" ], "date": "2026-05-08", "year": 2026, "summary": "Model the US-Soviet nuclear arms race as an iterated Prisoner's Dilemma in R, simulate strategy profiles including MAD, compare with stylised historical spending patterns, and connect to the folk theorem." }, { "id": "real-world-data-applications/cuban-missile-crisis-signaling-game", "title": "The Cuban Missile Crisis as a signaling game", "url": "tutorials/real-world-data-applications/cuban-missile-crisis-signaling-game/", "topic": "real-world-data-applications", "tags": [ "signaling-games", "incomplete-information", "crisis-bargaining" ], "labels": [ "applied-gt", "political-science" ], "date": "2026-05-08", "year": 2026, "summary": "Model the 1962 Cuban Missile Crisis as a game-theoretic signaling game in R, analyzing Kennedy's and Khrushchev's strategic choices through incomplete information, credibility, and escalation dynamics." }, { "id": "real-world-data-applications/penalty-kicks-minimax", "title": "Penalty kicks as a minimax game — testing mixed-strategy equilibrium with football data", "url": "tutorials/real-world-data-applications/penalty-kicks-minimax/", "topic": "real-world-data-applications", "tags": [ "minimax", "mixed-strategy", "sports-economics" ], "labels": [ "applied-gt", "zero-sum-games" ], "date": "2026-05-08", "year": 2026, "summary": "Model penalty kicks as a zero-sum game between kicker and goalkeeper, compute minimax mixed strategies from realistic scoring data, and test equilibrium predictions against observed professional football frequencies." }, { "id": "real-world-data-applications/spectrum-auction-analysis", "title": "Spectrum Auction Analysis: Revenue, Efficiency, and the Exposure Problem", "url": "tutorials/real-world-data-applications/spectrum-auction-analysis/", "topic": "real-world-data-applications", "tags": [ "auction-theory", "spectrum-auctions", "mechanism-design" ], "labels": [ "auctions", "applied" ], "date": "2026-05-08", "year": 2026, "summary": "Simulate and analyse multi-round ascending spectrum auction data inspired by FCC designs, computing winning prices, revenue efficiency, VCG benchmarks, bidder surplus, and diagnosing the exposure problem with complementary valuations." }, { "id": "real-world-data-applications/uber-surge-pricing-game", "title": "Uber surge pricing as a dynamic game", "url": "tutorials/real-world-data-applications/uber-surge-pricing-game/", "topic": "real-world-data-applications", "tags": [ "surge-pricing", "platform-economics", "dynamic-games" ], "labels": [ "surge-pricing", "platform", "dynamic-game" ], "date": "2026-05-08", "year": 2026, "summary": "Model ride-sharing surge pricing as a multi-player game between platform, drivers, and riders, simulating demand-supply dynamics, driver repositioning strategies, price equilibria, and welfare analysis." }, { "id": "reproducibility-open-science/docker-game-theory-environments", "title": "Docker and renv for Reproducible Game Theory Environments", "url": "tutorials/reproducibility-open-science/docker-game-theory-environments/", "topic": "reproducibility-open-science", "tags": [ "docker", "renv" ], "labels": [ "reproducibility", "devops" ], "date": "2026-05-08", "year": 2026, "summary": "Create fully reproducible computational environments for game theory research using Docker containers and renv package management, with reproducibility audit functions and environment comparison workflows." }, { "id": "reproducibility-open-science/literate-programming-game-theory", "title": "Literate programming for game theory research", "url": "tutorials/reproducibility-open-science/literate-programming-game-theory/", "topic": "reproducibility-open-science", "tags": [ "literate-programming", "quarto", "reproducibility" ], "labels": [ "reproducibility", "literate-programming", "quarto" ], "date": "2026-05-08", "year": 2026, "summary": "Best practices for reproducible game theory analysis using Quarto and R Markdown, covering document structure, parameterized reports, code-figure integration, and version control workflows for research projects." }, { "id": "reproducibility-open-science/preregistration-game-experiments", "title": "Preregistration and Pre-Analysis Plans for Game Theory Experiments", "url": "tutorials/reproducibility-open-science/preregistration-game-experiments/", "topic": "reproducibility-open-science", "tags": [ "preregistration", "experimental-design", "power-analysis" ], "labels": [ "methodology", "reproducibility" ], "date": "2026-05-08", "year": 2026, "summary": "How to create structured pre-analysis plans for game theory experiments, demonstrating that researcher degrees of freedom can flip conclusions about cooperation rates." }, { "id": "reproducibility-open-science/quarto-parameterized-reports", "title": "Quarto parameterized reports for game theory", "url": "tutorials/reproducibility-open-science/quarto-parameterized-reports/", "topic": "reproducibility-open-science", "tags": [ "quarto", "parameterized-reports", "reproducibility" ], "labels": [ "reproducibility", "workflow" ], "date": "2026-05-08", "year": 2026, "summary": "Use Quarto's params feature to create reusable game theory analyses that render multiple game variants --- Prisoner's Dilemma, Battle of the Sexes, Chicken --- from a single parameterized template." }, { "id": "reproducibility-open-science/reproducible-game-theory-workflow", "title": "Reproducible game theory research — a Quarto + renv workflow", "url": "tutorials/reproducibility-open-science/reproducible-game-theory-workflow/", "topic": "reproducibility-open-science", "tags": [ "renv", "quarto", "reproducibility" ], "labels": [ "reproducibility", "workflow", "renv" ], "date": "2026-05-08", "year": 2026, "summary": "Set up a fully reproducible game theory research project using renv for dependency management, Quarto for literate programming, and version control best practices for simulation-heavy analyses.\n" }, { "id": "simulations/agent-based-market-dynamics", "title": "Agent-based simulation of market dynamics — price discovery in a continuous double auction", "url": "tutorials/simulations/agent-based-market-dynamics/", "topic": "simulations", "tags": [ "agent-based-model", "market-microstructure", "price-discovery" ], "labels": [ "simulations", "market-design" ], "date": "2026-05-08", "year": 2026, "summary": "Build an agent-based model of a continuous double auction with zero-intelligence, trend-following, and fundamentalist traders, simulate price discovery and convergence to competitive equilibrium, and visualize how agent composition affects market efficiency and volatility." }, { "id": "simulations/cellular-automata-game-theory", "title": "Cellular automata and spatial game theory", "url": "tutorials/simulations/cellular-automata-game-theory/", "topic": "simulations", "tags": [ "spatial-games", "cellular-automata", "cooperation" ], "labels": [ "cellular-automata", "spatial", "simulation" ], "date": "2026-05-08", "year": 2026, "summary": "Implement spatial games on lattice grids where agents play the Prisoner's Dilemma with neighbors, exploring strategy invasion dynamics, cluster formation, and the Nowak-May spatial chaos phenomenon." }, { "id": "simulations/monte-carlo-game-equilibria", "title": "Monte Carlo methods for equilibrium computation", "url": "tutorials/simulations/monte-carlo-game-equilibria/", "topic": "simulations", "tags": [ "monte-carlo", "equilibrium-computation", "numerical-methods" ], "labels": [ "simulation-methods", "computational-gt" ], "date": "2026-05-08", "year": 2026, "summary": "Use Monte Carlo simulation in R to approximate Nash equilibria, estimate equilibrium payoffs under uncertainty, and validate analytical solutions through large-sample simulation experiments." }, { "id": "simulations/replicator-dynamics-simulation", "title": "Replicator Dynamics Simulation for Three-Strategy Games", "url": "tutorials/simulations/replicator-dynamics-simulation/", "topic": "simulations", "tags": [ "evolutionary-game-theory", "replicator-dynamics", "population-dynamics" ], "labels": [ "simulation", "evolutionary" ], "date": "2026-05-08", "year": 2026, "summary": "Large-scale replicator dynamics simulation for Rock-Paper-Scissors and other three-strategy games, comparing deterministic and stochastic dynamics across population sizes." }, { "id": "simulations/spatial-prisoners-dilemma-nowak-may", "title": "Spatial Prisoner's Dilemma on a lattice — Nowak & May 1992", "url": "tutorials/simulations/spatial-prisoners-dilemma-nowak-may/", "topic": "simulations", "tags": [ "prisoners-dilemma", "spatial-games", "agent-based" ], "labels": [ "spatial-dynamics", "cooperation" ], "date": "2026-05-08", "year": 2026, "summary": "Replicate the seminal Nowak & May (1992) spatial Prisoner's Dilemma on a 2D lattice in R, showing how spatial structure sustains cooperation through cluster formation." }, { "id": "statistical-foundations/bayesian-inference-game-parameters", "title": "Bayesian inference for game-theoretic parameters", "url": "tutorials/statistical-foundations/bayesian-inference-game-parameters/", "topic": "statistical-foundations", "tags": [ "bayesian-inference", "qre", "parameter-estimation" ], "labels": [ "bayesian", "estimation", "qre" ], "date": "2026-05-08", "year": 2026, "summary": "Estimate game parameters including payoffs, type distributions, and rationality levels from observed play using Bayesian methods with quantal response equilibrium likelihoods and grid-based posterior computation." }, { "id": "statistical-foundations/bootstrap-game-theory", "title": "Bootstrap inference for game-theoretic quantities", "url": "tutorials/statistical-foundations/bootstrap-game-theory/", "topic": "statistical-foundations", "tags": [ "bootstrap", "confidence-intervals", "shapley-value" ], "labels": [ "inference", "resampling" ], "date": "2026-05-08", "year": 2026, "summary": "Apply bootstrap resampling to construct confidence intervals for mixed-strategy frequency estimates and Shapley values, with coverage simulations comparing percentile and BCa methods." }, { "id": "statistical-foundations/hypothesis-testing-game-theoretic", "title": "Hypothesis testing as a game between nature and the statistician", "url": "tutorials/statistical-foundations/hypothesis-testing-game-theoretic/", "topic": "statistical-foundations", "tags": [ "hypothesis-testing", "minimax" ], "labels": [ "statistics", "minimax", "neyman-pearson" ], "date": "2026-05-08", "year": 2026, "summary": "Reframe classical hypothesis testing as a two-player minimax game in which nature chooses the true state and the statistician selects a decision rule. Derive the Neyman-Pearson lemma as the minimax optimal strategy and explore power analysis as strategic optimisation.\n" }, { "id": "statistical-foundations/hypothesis-testing-strategic", "title": "Hypothesis Testing in Strategic Environments", "url": "tutorials/statistical-foundations/hypothesis-testing-strategic/", "topic": "statistical-foundations", "tags": [ "hypothesis-testing", "nash-equilibrium", "permutation-test" ], "labels": [ "statistics", "methodology" ], "date": "2026-05-08", "year": 2026, "summary": "Frame statistical hypothesis testing as a game between researcher and Nature, implement permutation tests for Nash equilibrium deviations, and demonstrate multiple testing corrections across games." }, { "id": "statistical-foundations/maximum-likelihood-game-estimation", "title": "Maximum Likelihood Estimation of Game-Theoretic Models", "url": "tutorials/statistical-foundations/maximum-likelihood-game-estimation/", "topic": "statistical-foundations", "tags": [ "maximum-likelihood", "quantal-response-equilibrium" ], "labels": [ "statistics", "estimation" ], "date": "2026-05-08", "year": 2026, "summary": "Estimate the quantal response equilibrium (QRE) rationality parameter from experimental choice data using maximum likelihood, visualize the log-likelihood surface, and compare QRE with Nash equilibrium predictions." }, { "id": "time-series-econometrics/cointegration-strategic-long-run", "title": "Cointegration analysis of strategic long-run relationships", "url": "tutorials/time-series-econometrics/cointegration-strategic-long-run/", "topic": "time-series-econometrics", "tags": [ "cointegration", "vecm", "strategic-equilibrium" ], "labels": [ "cointegration", "time-series", "vecm" ], "date": "2026-05-08", "year": 2026, "summary": "Test for cointegration between strategic variables such as rival firm prices and competing military budgets using Engle-Granger and Johansen methods, and estimate vector error correction models for strategic adjustment dynamics." }, { "id": "time-series-econometrics/granger-causality-strategic", "title": "Granger causality in strategic interaction data", "url": "tutorials/time-series-econometrics/granger-causality-strategic/", "topic": "time-series-econometrics", "tags": [ "granger-causality", "cournot", "stackelberg" ], "labels": [ "time-series", "causality" ], "date": "2026-05-08", "year": 2026, "summary": "Apply Granger causality tests to detect strategic interdependence in time-series data, distinguishing simultaneous Cournot play from sequential Stackelberg leadership in simulated oligopoly settings." }, { "id": "time-series-econometrics/strategic-interaction-var-models", "title": "Modelling strategic interaction with VAR models", "url": "tutorials/time-series-econometrics/strategic-interaction-var-models/", "topic": "time-series-econometrics", "tags": [ "var", "granger-causality" ], "labels": [ "time-series", "var", "granger-causality" ], "date": "2026-05-08", "year": 2026, "summary": "Use vector autoregression to detect and model strategic interaction in time series data, with arms race dynamics as the motivating example. Granger causality tests reveal whether one actor's past behaviour predicts another's future choices, formalising the notion of strategic influence.\n" }, { "id": "time-series-econometrics/structural-estimation-oligopoly", "title": "Structural Estimation of Oligopoly Conduct Parameters", "url": "tutorials/time-series-econometrics/structural-estimation-oligopoly/", "topic": "time-series-econometrics", "tags": [ "structural-estimation", "oligopoly" ], "labels": [ "econometrics", "oligopoly" ], "date": "2026-05-08", "year": 2026, "summary": "Estimate the Bresnahan-Lau conjectural variations parameter from simulated Cournot oligopoly data using 2SLS/IV estimation, and compare conduct regimes from perfect competition to full collusion." }, { "id": "time-series-econometrics/var-models-strategic-interaction", "title": "VAR Models for Strategic Interaction Dynamics", "url": "tutorials/time-series-econometrics/var-models-strategic-interaction/", "topic": "time-series-econometrics", "tags": [ "var", "granger-causality", "oligopoly" ], "labels": [ "time-series", "econometrics" ], "date": "2026-05-08", "year": 2026, "summary": "Vector autoregression models capture dynamic strategic interdependence in oligopoly markets, revealing how firms' quantities today depend on rivals' past decisions through impulse response functions and Granger causality tests." }, { "id": "visualization-and-communication/ggplot2-advanced-annotations", "title": "Advanced ggplot2 Annotation Techniques for Game Theory Figures", "url": "tutorials/visualization-and-communication/ggplot2-advanced-annotations/", "topic": "visualization-and-communication", "tags": [ "ggplot2", "annotations" ], "labels": [ "visualization", "ggplot2" ], "date": "2026-05-08", "year": 2026, "summary": "Master publication-quality game theory diagrams with Nash equilibrium labels, best-response arrows, payoff region shading, and mathematical annotations using ggplot2." }, { "id": "visualization-and-communication/interactive-game-theory-dashboards", "title": "Interactive game theory dashboards with plotly", "url": "tutorials/visualization-and-communication/interactive-game-theory-dashboards/", "topic": "visualization-and-communication", "tags": [ "plotly", "interactive-visualization", "replicator-dynamics" ], "labels": [ "visualization-and-communication", "tools" ], "date": "2026-05-08", "year": 2026, "summary": "Build advanced interactive visualisations for game theory using plotly in R: animated replicator dynamics, hover-enabled payoff matrices, linked strategy-payoff views, and 3D expected-payoff surfaces over the mixed-strategy simplex." }, { "id": "visualization-and-communication/network-visualization-igraph", "title": "Network visualization for games with igraph", "url": "tutorials/visualization-and-communication/network-visualization-igraph/", "topic": "visualization-and-communication", "tags": [ "network-analysis", "igraph", "game-visualization" ], "labels": [ "network", "visualization", "igraph" ], "date": "2026-05-08", "year": 2026, "summary": "Visualize game-theoretic interaction structures using igraph in R, including best-response networks, Nash equilibrium connectivity, and centrality analysis of strategic players." }, { "id": "visualization-and-communication/publication-ready-ggplot-theme", "title": "Publication-ready ggplot2 figures with theme_publication()", "url": "tutorials/visualization-and-communication/publication-ready-ggplot-theme/", "topic": "visualization-and-communication", "tags": [ "ggplot2", "theme", "colorblind-safe" ], "labels": [ "visualization", "reproducible-style" ], "date": "2026-05-08", "year": 2026, "summary": "Build a complete publication-ready ggplot2 theme from scratch, demonstrating the Okabe-Ito colorblind-safe palette, dual PDF/PNG export, and consistent styling across all figure types used in this site." }, { "id": "visualization-and-communication/shiny-game-theory-apps", "title": "Building Shiny Apps for Interactive Game Theory Exploration", "url": "tutorials/visualization-and-communication/shiny-game-theory-apps/", "topic": "visualization-and-communication", "tags": [ "shiny", "interactive", "game-solver" ], "labels": [ "visualization", "interactive" ], "date": "2026-05-08", "year": 2026, "summary": "Complete Shiny app code for a 2x2 game solver, Cournot duopoly simulator, and evolutionary dynamics visualiser, with static ggplot2 recreations for the tutorial." } ], "edges": [ { "source": "tutorials/two-by-two-nash-explorer-tutorial", "target": "foundations/nash-equilibrium-mixed", "weight": 2 }, { "source": "tutorials/two-by-two-nash-explorer-tutorial", "target": "foundations/trembling-hand-refinement", "weight": 2 }, { "source": "tutorials/two-by-two-nash-explorer-tutorial", "target": "history-of-gt-mathematics/nash-equilibrium-original-proof", "weight": 2 }, { "source": "tutorials/two-by-two-nash-explorer-tutorial", "target": "history-of-gt-mathematics/selten-trembling-hand-perfection", "weight": 2 }, { "source": "tutorials/two-by-two-nash-explorer-tutorial", "target": "ml-and-gt/fictitious-play-convergence", "weight": 2 }, { "source": "tutorials/two-by-two-nash-explorer-tutorial", "target": "optimization-numerical-methods/gradient-descent-nash-finding", "weight": 2 }, { "source": "tutorials/two-by-two-nash-explorer-tutorial", "target": "optimization-numerical-methods/simulated-annealing-equilibria", "weight": 2 }, { "source": "tutorials/two-by-two-nash-explorer-tutorial", "target": "optimization-numerical-methods/support-enumeration-algorithm", "weight": 4 }, { "source": "tutorials/two-by-two-nash-explorer-tutorial", "target": "public-apis-and-datasets/kaggle-competition-strategic", "weight": 2 }, { "source": "tutorials/two-by-two-nash-explorer-tutorial", "target": "r-package-development/testing-game-theory-code", "weight": 2 }, { "source": "tutorials/two-by-two-nash-explorer-tutorial", "target": "statistical-foundations/hypothesis-testing-strategic", "weight": 2 }, { "source": "tutorials/two-by-two-nash-explorer-tutorial", "target": "visualization-and-communication/shiny-game-theory-apps", "weight": 2 }, { "source": "ai-ml-foundations-and-applications/gans-minimax-game", "target": "classical-games/matching-pennies", "weight": 2 }, { "source": "ai-ml-foundations-and-applications/gans-minimax-game", "target": "foundations/zero-sum-minimax-theorem", "weight": 4 }, { "source": "ai-ml-foundations-and-applications/gans-minimax-game", "target": "linear-algebra-matrix/lp-duality-zero-sum", "weight": 2 }, { "source": "ai-ml-foundations-and-applications/gans-minimax-game", "target": "ml-and-gt/adversarial-robustness-games", "weight": 2 }, { "source": "ai-ml-foundations-and-applications/gans-minimax-game", "target": "real-world-data-applications/penalty-kicks-minimax", "weight": 2 }, { "source": "ai-ml-foundations-and-applications/gans-minimax-game", "target": "statistical-foundations/hypothesis-testing-game-theoretic", "weight": 2 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "auction-theory-deep-dive/english-ascending-auction", "weight": 1 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "auction-theory-deep-dive/gsp-auction", "weight": 3 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "auction-theory-deep-dive/revenue-equivalence", "weight": 3 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "bayesian-methods/auction-optimal-reserve-prices", "weight": 1 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "bayesian-methods/information-design-persuasion", "weight": 1 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "case-studies/spectrum-auction-design", "weight": 2 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "cryptography-and-gt/blockchain-consensus-game", "weight": 1 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "cryptography-and-gt/commitment-schemes-game-theory", "weight": 2 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "cryptography-and-gt/secure-multiparty-computation", "weight": 3 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "ethics-and-game-theory/organ-donation-mechanism", "weight": 2 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "ethics-and-game-theory/voting-paradoxes-strategic", "weight": 3 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "ethics-applications/ai-alignment-principal-agent", "weight": 1 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "ethics-applications/algorithmic-fairness-game-theory", "weight": 3 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "ethics-applications/privacy-game-theory", "weight": 2 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "foundations/revelation-principle", "weight": 3 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "mechanism-design/combinatorial-auctions", "weight": 1 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "mechanism-design/deferred-acceptance", "weight": 1 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "mechanism-design/matching-markets-practical", "weight": 1 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "mechanism-design/mechanism-design-intro", "weight": 1 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "mechanism-design/vcg-mechanism", "weight": 1 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "mechanism-design/vickrey-second-price-auction", "weight": 3 }, { "source": "ai-ml-foundations-and-applications/mechanism-design-ml-auctions", "target": "real-world-data-applications/spectrum-auction-analysis", "weight": 2 }, { "source": "ai-ml-foundations-and-applications/multi-armed-bandits-exploration", "target": "ml-and-gt/deep-reinforcement-learning-games", "weight": 2 }, { "source": "ai-ml-foundations-and-applications/multi-armed-bandits-exploration", "target": "ml-and-gt/multi-agent-reinforcement-learning", "weight": 2 }, { "source": "ai-ml-foundations-and-applications/multi-armed-bandits-exploration", "target": "public-apis-and-datasets/openai-gym-game-environments", "weight": 2 }, { "source": "ai-ml-foundations-and-applications/perceptron-to-deep-learning-historical-r-implementation", "target": "ml-and-gt/deep-reinforcement-learning-games", "weight": 2 }, { "source": "ai-ml-foundations-and-applications/shap-values-cooperative-games", "target": "cooperative-gt/coalition-formation-hedonic", "weight": 1 }, { "source": "ai-ml-foundations-and-applications/shap-values-cooperative-games", "target": "cooperative-gt/shapley-shubik-power", "weight": 3 }, { "source": "ai-ml-foundations-and-applications/shap-values-cooperative-games", "target": "cooperative-gt/shapley-value", "weight": 2 }, { "source": "ai-ml-foundations-and-applications/shap-values-cooperative-games", "target": "ml-and-gt/deep-reinforcement-learning-games", "weight": 1 }, { "source": "ai-ml-foundations-and-applications/shap-values-cooperative-games", "target": "ml-and-gt/multi-agent-reinforcement-learning", "weight": 1 }, { "source": "ai-ml-foundations-and-applications/shap-values-cooperative-games", "target": "ml-and-gt/no-regret-learning-games", "weight": 1 }, { "source": "ai-ml-foundations-and-applications/shap-values-cooperative-games", "target": "public-apis-and-datasets/openai-gym-game-environments", "weight": 1 }, { "source": "ai-ml-foundations-and-applications/shap-values-cooperative-games", "target": "statistical-foundations/bootstrap-game-theory", "weight": 2 }, { "source": "auction-theory-deep-dive/all-pay-auction-lobbying", "target": "auction-theory-deep-dive/common-value-winners-curse", "weight": 2 }, { "source": "auction-theory-deep-dive/all-pay-auction-lobbying", "target": "auction-theory-deep-dive/first-price-sealed-bid", "weight": 2 }, { "source": "auction-theory-deep-dive/all-pay-auction-lobbying", "target": "auction-theory-deep-dive/gsp-auction", "weight": 2 }, { "source": "auction-theory-deep-dive/all-pay-auction-lobbying", "target": "auction-theory-deep-dive/revenue-equivalence", "weight": 2 }, { "source": "auction-theory-deep-dive/all-pay-auction-lobbying", "target": "bayesian-methods/auction-common-value-estimation", "weight": 1 }, { "source": "auction-theory-deep-dive/all-pay-auction-lobbying", "target": "bayesian-methods/auction-optimal-reserve-prices", "weight": 1 }, { "source": "auction-theory-deep-dive/all-pay-auction-lobbying", "target": "classical-games/war-of-attrition-sealed", "weight": 2 }, { "source": "auction-theory-deep-dive/all-pay-auction-lobbying", "target": "mechanism-design/combinatorial-auctions", "weight": 1 }, { "source": "auction-theory-deep-dive/all-pay-auction-lobbying", "target": "mechanism-design/vcg-mechanism", "weight": 1 }, { "source": "auction-theory-deep-dive/all-pay-auction-lobbying", "target": "mechanism-design/vickrey-second-price-auction", "weight": 1 }, { "source": "auction-theory-deep-dive/common-value-winners-curse", "target": "auction-theory-deep-dive/first-price-sealed-bid", "weight": 2 }, { "source": "auction-theory-deep-dive/common-value-winners-curse", "target": "auction-theory-deep-dive/gsp-auction", "weight": 2 }, { "source": "auction-theory-deep-dive/common-value-winners-curse", "target": "auction-theory-deep-dive/revenue-equivalence", "weight": 2 }, { "source": "auction-theory-deep-dive/common-value-winners-curse", "target": "bayesian-methods/auction-common-value-estimation", "weight": 1 }, { "source": "auction-theory-deep-dive/common-value-winners-curse", "target": "bayesian-methods/auction-optimal-reserve-prices", "weight": 1 }, { "source": "auction-theory-deep-dive/common-value-winners-curse", "target": "bayesian-methods/information-design-persuasion", "weight": 1 }, { "source": "auction-theory-deep-dive/common-value-winners-curse", "target": "mechanism-design/combinatorial-auctions", "weight": 1 }, { "source": "auction-theory-deep-dive/common-value-winners-curse", "target": "mechanism-design/vcg-mechanism", "weight": 1 }, { "source": "auction-theory-deep-dive/common-value-winners-curse", "target": "mechanism-design/vickrey-second-price-auction", "weight": 1 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "auction-theory-deep-dive/gsp-auction", "weight": 2 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "auction-theory-deep-dive/revenue-equivalence", "weight": 2 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "bayesian-methods/auction-optimal-reserve-prices", "weight": 1 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "bayesian-methods/information-design-persuasion", "weight": 1 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "classical-games/prisoners-dilemma-formal", "weight": 2 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "classical-games/war-of-attrition-sealed", "weight": 1 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "cryptography-and-gt/blockchain-consensus-game", "weight": 1 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "cryptography-and-gt/secure-multiparty-computation", "weight": 1 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "ethics-and-game-theory/voting-paradoxes-strategic", "weight": 1 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "ethics-applications/ai-alignment-principal-agent", "weight": 1 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "ethics-applications/algorithmic-fairness-game-theory", "weight": 1 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "foundations/revelation-principle", "weight": 1 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "mechanism-design/combinatorial-auctions", "weight": 1 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "mechanism-design/deferred-acceptance", "weight": 1 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "mechanism-design/matching-markets-practical", "weight": 1 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "mechanism-design/mechanism-design-intro", "weight": 1 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "mechanism-design/vcg-mechanism", "weight": 1 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "mechanism-design/vickrey-second-price-auction", "weight": 3 }, { "source": "auction-theory-deep-dive/english-ascending-auction", "target": "real-world-data-applications/spectrum-auction-analysis", "weight": 1 }, { "source": "auction-theory-deep-dive/first-price-sealed-bid", "target": "auction-theory-deep-dive/gsp-auction", "weight": 2 }, { "source": "auction-theory-deep-dive/first-price-sealed-bid", "target": "auction-theory-deep-dive/revenue-equivalence", "weight": 2 }, { "source": "auction-theory-deep-dive/first-price-sealed-bid", "target": "bayesian-methods/auction-common-value-estimation", "weight": 1 }, { "source": "auction-theory-deep-dive/first-price-sealed-bid", "target": "bayesian-methods/auction-optimal-reserve-prices", "weight": 1 }, { "source": "auction-theory-deep-dive/first-price-sealed-bid", "target": "mechanism-design/combinatorial-auctions", "weight": 1 }, { "source": "auction-theory-deep-dive/first-price-sealed-bid", "target": "mechanism-design/vcg-mechanism", "weight": 1 }, { "source": "auction-theory-deep-dive/first-price-sealed-bid", "target": "mechanism-design/vickrey-second-price-auction", "weight": 1 }, { "source": "auction-theory-deep-dive/gsp-auction", "target": "auction-theory-deep-dive/revenue-equivalence", "weight": 5 }, { "source": "auction-theory-deep-dive/gsp-auction", "target": "bayesian-methods/auction-common-value-estimation", "weight": 1 }, { "source": "auction-theory-deep-dive/gsp-auction", "target": "bayesian-methods/auction-optimal-reserve-prices", "weight": 2 }, { "source": "auction-theory-deep-dive/gsp-auction", "target": "bayesian-methods/information-design-persuasion", "weight": 1 }, { "source": "auction-theory-deep-dive/gsp-auction", "target": "case-studies/spectrum-auction-design", "weight": 2 }, { "source": "auction-theory-deep-dive/gsp-auction", "target": "cryptography-and-gt/blockchain-consensus-game", "weight": 1 }, { "source": "auction-theory-deep-dive/gsp-auction", "target": "cryptography-and-gt/commitment-schemes-game-theory", "weight": 2 }, { "source": "auction-theory-deep-dive/gsp-auction", "target": "cryptography-and-gt/secure-multiparty-computation", "weight": 3 }, { "source": "auction-theory-deep-dive/gsp-auction", "target": "ethics-and-game-theory/organ-donation-mechanism", "weight": 2 }, { "source": "auction-theory-deep-dive/gsp-auction", "target": "ethics-and-game-theory/voting-paradoxes-strategic", "weight": 3 }, { "source": "auction-theory-deep-dive/gsp-auction", "target": "ethics-applications/ai-alignment-principal-agent", "weight": 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