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Complete information

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Complete information

thumb|[[prisoner's-dilemma, a typical example of complete information]] In economics and game-theory, complete information is an economic situation or game in which knowledge about other market participants or players is available to all participants. The utility functions (including risk aversion), payoffs, strategies and "types" of players are thus common knowledge. Complete information is the concept that each player in the game is aware of the sequence, strategies, and payoffs throughout gameplay. Given this information, the players have the ability to plan accordingly based on the information to maximize their own strategies and utility at the end of the game. A typical example is the prisoner's-dilemma.

Inversely, in a game with incomplete information, players do not possess full information about other players. Some players possess private information, a fact that the others should take into account when forming expectations about how those players will behave. A typical example is an auction: each player knows their own utility function (valuation for the item), but does not know the utility function of the other players.

Applications Games of incomplete information arise frequently in social science. For instance, john-harsanyi was motivated by consideration of arms control negotiations, where the players may be uncertain both of the capabilities of their opponents and of their desires and beliefs.

It is often assumed that the players have some statistical information about the other players, e.g. in an auction, each player knows that the valuations of the other players are drawn from some probability distribution. In this case, the game is called a bayesian-game.

In games that have a varying degree of complete information and game type, there are different methods available to the player to solve the game based on this information. In games with static, complete information, the approach to solve is to use nash-equilibrium to find viable strategies. In dynamic games with complete information, backward-induction is the solution concept, which eliminates non-credible threats as potential strategies for players.

A classic example of a dynamic game with complete information is Stackelberg's (1934) sequential-move version of Cournot duopoly. Other examples include Leontief's (1946) monopoly-union model and Rubenstein's bargaining model.

Lastly, when complete information is unavailable (incomplete information games), these solutions turn towards Bayesian Nash Equilibria since games with incomplete information become Bayesian games. A game with complete information may or may not have perfect information, and vice versa.

See also *[[bayesian-game]] *Handicap principle *Market impact *[[screening-game]] *[[signaling-game]] *Small talk *Trash-talk

References ## Bibliography Watson, J. (2015) Strategy: An Introduction to Game Theory.* Volume 139. New York, WW Norton Fudenberg, D. and [[jean-tirole|Tirole, J.]] (1993) Game Theory*. MIT Press. (see Chapter 6, sect 1) Gibbons, R. (1992) A primer in game theory*. Harvester-Wheatsheaf. (see Chapter 3) * Ian Frank, David Basin (1997), Artificial Intelligence 100 (1998) 87-123. "Search in games with incomplete information: a case study using Bridge card play".