The New Palgrave Dictionary of Economics

2018 Edition
| Editors: Macmillan Publishers Ltd

Individual Learning in Games

  • Teck H. Ho
Reference work entry


This article reviews individual models of learning in games. We show that the experience-weighted attraction (EWA) learning nests different forms of reinforcement and belief learning, and that belief learning is mathematically equivalent to generalized reinforcement, where even unchosen strategies are reinforced. Many studies consisting of thousands of observations suggest that the EWA model predicts behaviour out-of-sample better than its special cases. We also describe a generalization of EWA learning to investigate anticipation by some players that others are learning. This generalized framework links equilibrium and learning models, and improves predictive performance when players are experienced and sophisticated.


Belief learning Curse of knowledge Equilibrium Experience-weighted attraction (EWA) learning Extensive-form games Fictitious play Forgone payoffs Individual learning in games Individual models of learning Maximum likelihood Mixed-strategy equilibrium Noise Overconfidence Population models of learning Quantal response equilibrium Reinforcement learning Signalling Social calibration Sophisticated players 

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© Macmillan Publishers Ltd. 2018

Authors and Affiliations

  • Teck H. Ho
    • 1
  1. 1.