Past exam of the mathematics course of the University of Cambridge 2014 ib Paper 2 9H Solution Created 2026-09-24 Updated 2026-10-06
In a two-player zero-sum game, the row player chooses a row, the column player chooses a column, and the row player's gain is the column player's loss. If their independent mixed strategies are probability vectors , , the row player's expected payoff is .
The optimal mixed strategies solveThe minimax theorem equates these two guaranteed values. Equivalently, for a value , and componentwise.
For a row strategy , the payoffs against the two pure columns are and . Their minimum is maximized at their intersection, , where both are . Symmetrically the column player's maximum of the two row payoffs is minimized at . HenceThese probabilities are unique: moving either probability away from worsens that player's guaranteed payoff.
Past exam of the mathematics course of the University of Cambridge 2016 ib Paper 1 8H Solution Created 2026-09-24 Updated 2026-10-06
Let be the row player's mixed strategy and the column player's mixed strategy. The fourth row is strictly dominated by the first. A useful candidate mixes the first two rows so that their first and third column payoffs agree. If the first row has probability , these payoffs are and , giving and common value zero.
To prove that these are optimal mixed strategies, use the two explicit mixed strategiesTheir payoff vectors satisfyThus the row player guarantees a payoff at least zero against every column mixed strategy, and the column player guarantees a payoff at most zero against every row mixed strategy. This matching pair proves that the value of the zero-sum game is zero.
These optimal mixed strategies are also unique. Since is strictly negative in rows three and four, any optimal row strategy gives them probability zero. Against columns one and three it must then satisfy both and , so . Similarly, is strictly positive in column two, forcing an optimal column strategy to avoid that column; its constraints against rows one and two then force equal weights on columns one and three.
Past exam of the mathematics course of the University of Cambridge 2017 ib Paper 3 21H a Solution Created 2026-09-24 Updated 2026-10-05
In a matrix game, entry is the row player's payoff, and the column player's payoff is . A mixed strategy is a probability vector over the available rows or columns. With strategies , the row payoff is . Its optimal mixed strategy maximizes its guaranteed payoff, while the column player minimizes the largest row payoff:The equality is the finite minimax theorem. Equivalently the row player maximizes , and the column player minimizes . Each optimal strategy guarantees its corresponding bound against every opponent strategy; for the column player's own negative payoff this is also a maximin strategy.
Past exam of the mathematics course of the University of Cambridge 2021 ib Paper 3 19H Solution Created 2026-09-24 Updated 2026-09-25
An matrix game with payoff matrix is a two-player zero-sum game: player I chooses a row and receives , while player II chooses a column and loses the same amount. For mixed strategies and , the expected payoff to player I isPlayer I's optimal mixed strategy maximizes the payoff guaranteed against every , while player II's minimizes the largest payoff obtainable by any . Thusby the minimax theorem. Equivalently, optimal strategies satisfy
Here , so this is an antisymmetric zero-sum game. For every probability vector ,It follows that the row player's guaranteed payoff cannot exceed zero and the column player's worst loss cannot be below zero. Minimax therefore givesIf is optimal for player I, thenTransposing and using giveswhich is precisely the optimality condition for player II. Thus every optimal strategy for player I is also optimal for player II.
The condition explicitly readsThe probability vectorsatisfiesso it is optimal for both players.
To prove uniqueness, let be any optimal strategy. Since is optimal for player II and is optimal for player I,and hence . Writing , the first, second, and fourth inequalities in giveConsequentlyso equality holds throughout: and . The normalization yields . Therefore the displayed is the unique optimal strategy.