Encyclopedia of Complexity and Systems Science

Living Edition
| Editors: Robert A. Meyers

Bayesian Games: Games with Incomplete Information

Living reference work entry
DOI: https://doi.org/10.1007/978-3-642-27737-5_29-3


Bayesian games (also known as Games with Incomplete Information) are models of interactive decision situations in which the decision makers (players) have only partial information about the data of the game and about the other players. Clearly this is typically the situation we are facing and hence the importance of the subject: The basic underlying assumption of classical game theory according to which the data of the game is common knowledge(CK) among the players is too strong and often implausible in real situations. The importance of Bayesian games is in providing the tools and methodology to relax this implausible assumption, to enable modeling of the overwhelming majority of real-life situations in which players have only partial information about the payoff relevant data. As a result of the interactive nature of the situation, this methodology turns out to be rather deep and sophisticated, both conceptually and mathematically. Adopting the classical Bayesian...


Nash Equilibrium Incomplete Information Payoff Function Mixed Strategy Belief Structure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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I am grateful to two anonymous reviewers for their helpful comments.


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© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Center for the Study of RationalityHebrew UniversityJerusalemIsrael