Experience-weighted attraction learning in normal form games

Article Abstract:

A general 'experience-weighted attraction' model has been developed and its parameters have been estimated by using three sets of experimental data. It combines elements of belief-based models and choice reinforcement. A key feature of the model is a parameter that weighs the strength of hypothetical reinforcement of strategies that were not chosen according to the payoff they would have yielded, relative to reinforcement of chosen strategies according to received payoffs. Two other key features are two discount rates which separate discount previous attractions and an experience weight.

Models, Investments, Equilibrium (Economics)

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Prediction, optimization, and learning in repeated games

Article Abstract:

The Bayesian learning model in repeated games points out an obstacle to the Nash equilibrium conjecture that players will learn to play in an equilibrium through repeated interaction. An analysis of the Bayesian model showed that when players' beliefs are cautious, each will choose a supportive strategy that will lead them to predict the continuation path of the play. Results also showed that if players in repetitive games optimize in terms of beliefs to fulfill and satisfy a neutrality condition, then every player will select a strategy that his opponent was certain would not played.

Commercial printing, lithographic, Econometrics & Model Building, Analysis, Econometrics, Business models

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Extensive form reasoning in normal form games

Article Abstract:

An analysis ofextensive form reasoning in normal form games is presented. The analysis focuses on the development of the strategic independence concept. It is shown that such independence is simulated by the reduced normal form and can apply tonormal form information set and subgame descriptions. In addition, a relationship between normal forms and their extensive form counterparts can be established.

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