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Preprints, Working Papers, ... Year : 2023

Calibrated Clustering and Analogy-Based Expectation Equilibrium

Abstract

Families of normal-form two-player games are categorized by players into K analogy classes applying the K-means clustering technique to the data generated by the distributions of opponent's behavior. This results in Calibrated Analogy-Based Expectation Equilibria in which strategies are analogy-based expectation equilibria given the analogy partitions and analogy partitions are derived from the strategies by the K-means clustering algorithm. We discuss various concepts formalizing this, and observe that distributions over analogy partitions are sometimes required to guarantee existence. Applications to games with linear best-responses are discussed highlighting the differences between strategic complements and strategic substitutes.
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Dates and versions

halshs-04154234 , version 1 (06-07-2023)

Identifiers

  • HAL Id : halshs-04154234 , version 1

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Philippe Jehiel, Giacomo Weber. Calibrated Clustering and Analogy-Based Expectation Equilibrium. 2023. ⟨halshs-04154234⟩
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