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Bimatrix game

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In game theory, a bimatrix game is a simultaneous game for two players in which each player has a finite number of possible actions. The name comes from the fact that the normal form of such a game can be described by two matrixes - matrix A describing the payoffs of player 1 and matrix B describing the payoffs of player 2.

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Player 1 is often called the "row player" and player 2 the "column player". If player 1 has m possible actions and player 2 n possible actions, then each of the two matrixes has m rows by n columns. when the row player selects the i -th action and the column player selects the j -th action, the payoff to the row player is A [ i , j ] and the payoff to the column player is B [ i , j ] .

The players can also play mixed strategies. A mixed strategy for the row player is a non-negative vector x of length m such that: i = 1 m x i = 1 . Similarly, a mixed strategy for the column player is a non-negative vector y of length m such that: j = 1 m y j = 1 . When the players play mixed strategies with vectors x and y, the expected payoff of the row player is: x T A y and of the column player: x T B y .

Nash equilibrium in bimatrix games

Every bimatrix game has a Nash equilibrium in (possibly) mixed strategies. Finding such a Nash equilibrium is a special case of the Linear complementarity problem and can be done in finite time by the Lemke–Howson algorithm.

There is a reduction from the problem of finding a Nash equilibrium in a bimatrix game to the problem of finding a competitive equilibrium in an economy with Leontief utilities.

A zero-sum game is a special case of a bimatrix game in which A + B = 0 .

References

Bimatrix game Wikipedia