Decision Tree — Choosing the Right Game-Theoretic Model

An interactive guide to selecting the appropriate game-theoretic model or solution concept for your problem.

Decision Tree

Not sure which game-theoretic model fits your problem? This decision tree walks you through a series of questions about your strategic interaction and recommends the appropriate framework and solution concept.

How to use

  1. Decision Assistant — an interactive wizard that asks questions one at a time and recommends a model with links to the relevant tutorials.
  2. Decision Tree (chart) — a static flowchart showing all paths at once.

Key decision points

The tree covers these major branching questions:

  • Are moves simultaneous or sequential? Determines normal-form vs. extensive-form representation.
  • Is information complete? Leads to Bayesian game formulations.
  • Is the game zero-sum? Points to minimax theorem and linear programming solutions.
  • Is the game repeated? Branches into finite vs. infinite horizon and folk theorem territory.
  • Are payoffs transferable? Separates cooperative (TU/NTU) from non-cooperative games.
  • Is there a designer? Enters mechanism design, matching, and voting.

Data

The decision tree is generated by R/build_decision_tree.R and stored as JSON at artifacts/decision-tree.json.

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