Linear Programming and Game Theory 2 (AQA A-Level Further Maths): Flashcards

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Games as Linear Programming Problems
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Zero-sum game definition

One player's gain equals other's loss; total payoff sums to zero

Pay-off matrix shows

Outcomes from row player's (player A's) perspective

Row player's play-safe strategy (maximin)

Maximum of row minima

Column player's play-safe strategy (minimax)

Minimum of column maxima

Stable solution condition for pure strategy

Max of row minima = min of column maxima

Expected payoff formula

E(x)=i=1nxipiE(x) = \sum_{i=1}^{n} x_ip_i where pi=1\sum p_i = 1

If pay-off matrix has negative entries

Add constant to all entries to make non-negative

After solving LP, must do this to get true game value

Subtract the constant added initially

Dominance in zero-sum games

Row/column with all better entries can eliminate another

Objective function in LP for zero-sum game

Maximise P=vP = v where vv is value of game

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