Game theory bayesian updating


30-Apr-2020 12:22

The probability associated with a type is the probability that the player, for whom the type is specified, is that type.In a Bayesian game, the incompleteness of information means that at least one player is unsure of the type (and so the payoff function) of another player.In a Bayesian game, one has to specify strategy spaces, type spaces, payoff functions and beliefs for every player.A strategy for a player is a complete plan of action that covers every contingency that might arise for every type that player might be.The new equilibrium concept achieves consistencies in results among different types of games that current games theory at times fails to.

A Bayesian game can be converted into a game of complete but imperfect information under the "common prior assumption". Harsanyi describes a Bayesian game in the following way.

He previously held research and teaching positions in Academia Sinica, National Taiwan University and Nanyang Technological University.

In game theory, a Bayesian game is a game in which the players have incomplete information on the other players (e.g.

Each belief is the probability of the other players having particular types, given the type of the player with that belief (i.e. The definition of Bayesian games has been combined with stochastic games to allow for environment states (e.g.

physical world states) and stochastic transitions between states.

In a BEIC, conjectures are consistent with the equilibrium or equilibriums they supported and so rationality is achieved for actions, strategies and beliefs and (statistical) decision rule.



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