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Bayesian Games: Games with Incomplete Information

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Abbreviations

Bayesian equilibrium:

A Nash equilibrium of a Bayesian game: A list of behavior and beliefs such that each player is doing his best to maximize his payoff, according to his beliefs about the behavior of the other players.

Bayesian game:

An interactive decision situation involving several decision makers (players) in which each player has beliefs about (i.e., assigns probability distribution to) the payoff relevant parameters and the beliefs of the other players.

Common prior and consistent beliefs:

The beliefs of players in a game with incomplete information are said to be consistent if they are derived from the same probability distribution (the common prior) by conditioning on each player’s private information. In other words, if the beliefs are consistent, the only source of differences in beliefs is difference in information.

Correlated equilibrium:

A Nash equilibrium in an extension of the game in which there is a chance move, and each player has only partial information about its outcome.

State of nature:

Payoff relevant data of the game such as payoff functions, value of a random variable, etc. It is convenient to think of a state of nature as a full description of a “game-form” (actions and payoff functions).

State of the world:

A specification of the state of nature (payoff relevant parameters) and the players’ types (belief of all levels). That is, a state of the world is a state of nature and a list of the states of mind of all players.

Type:

Also known as state of mind and is a full description of player’s beliefs (about the state of nature), beliefs about beliefs of the other players, beliefs about the beliefs about his beliefs, etc. ad infinitum.

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Acknowledgments

I am grateful to two anonymous reviewers for their helpful comments.

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Correspondence to Shmuel Zamir .

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© 2013 Springer Science+Business Media New York

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Zamir, S. (2013). Bayesian Games: Games with Incomplete Information. In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, New York, NY. https://doi.org/10.1007/978-3-642-27737-5_29-3

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