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Article . 2013 . Peer-reviewed
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Article . 2013
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Modeling of the learning process in centipede games

Authors: Westveld, Anton H.; Hoff, Peter D.;

Modeling of the learning process in centipede games

Abstract

AbstractAccording to classic game theory, individuals playing a centipede game learn about the subgame perfect Nash equilibrium via repeated play of the game. We employ statistical modeling to evaluate the evidence of such learning processes while accounting for the substantial within‐player correlation observed for the players’ decisions and rates of learning. We determine the probabilities of players’ choices through a quantal response equilibrium. Our statistical approach additionally (i) relaxes the assumption of players’ a priori global knowledge of opponents’ strategies, (ii) incorporates within‐subject dependency through random effects, and (iii) allows players’ decision probabilities to change with repeated play through an explicit covariate. Hence, players’ tendencies to correctly assess the utility of decisions are allowed to evolve over the course of the game, and both adaptive behavior as one accrues experience and the difference in this behavior between players are appropriately reflected by the model. Copyright © 2013 John Wiley & Sons Ltd

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Keywords

game theory, interaction/relational data, quantal response equilibrium, Statistics, Bayesian inference, hierarchical modeling

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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