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Solution
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Solution provided by AtoZmath.com
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Game Theory problem using matrix method calculator
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1. Find the solution of game using matrix method for the following pay-off matrix
| | | Player B | | | | | | B_1 | B_2 | B_3 | | | Player A | A_1 | | 1 | 7 | 2 | | A_2 | | 6 | 2 | 7 | | A_3 | | 5 | 1 | 6 | |
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Example1. Find Solution of game theory problem using matrix method
Player A\Player B | B1 | B2 | B3 | A1 | 1 | 7 | 2 | A2 | 6 | 2 | 7 | A3 | 5 | 1 | 6 | Solution:1. Saddle point testing Players | | | Player B | | | | | | B_1 | B_2 | B_3 | | | Player A | A_1 | | 1 | 7 | 2 | | A_2 | | 6 | 2 | 7 | | A_3 | | 5 | 1 | 6 | |
We apply the maximin (minimax) principle to analyze the game. | | | Player B | | | | | | B_1 | B_2 | B_3 | | Row Minimum | Player A | A_1 | | 1 | 7 | 2 | | 1 | A_2 | | (6) | [2] | 7 | | [2] | A_3 | | 5 | 1 | 6 | | 1 | | Column Maximum | | (6) | 7 | 7 | | |
Select minimum from the maximum of columns Column MiniMax = (6) Select maximum from the minimum of rows Row MaxiMin = [2] Here, Column MiniMax != Row MaxiMin :. This game has no saddle point.
2. Dominance rule to reduce the size of the payoff matrix Using dominance property | | | Player B | | | | | | B_1 | B_2 | B_3 | | | Player A | A_1 | | 1 | 7 | 2 | | A_2 | | 6 | 2 | 7 | | A_3 | | 5 | 1 | 6 | |
row-3 <= row-2, so remove row-3 | | | Player B | | | | | | B_1 | B_2 | B_3 | | | Player A | A_1 | | 1 | 7 | 2 | | A_2 | | 6 | 2 | 7 | |
column-3 >= column-1, so remove column-3 | | | Player B | | | | | | B_1 | B_2 | | | Player A | A_1 | | 1 | 7 | | A_2 | | 6 | 2 | |
reduced matrix | | | Player B | | | | | | B_1 | B_2 | | | Player A | A_1 | | 1 | 7 | | A_2 | | 6 | 2 | |
For this reduced matrix, calculate P_(Adj) and P_(Cof)P_(Adj) = [[2,-7],[-6,1]]and P_(Cof) = [[2,-6],[-7,1]]Player A's optimal strategies =([[1,1]] xx P_(Adj))/([[1,1]] xx P_(Adj) xx [[1],[1]])=([[1,1]][[2,-7],[-6,1]])/([[1,1]][[2,-7],[-6,1]][[1],[1]])=([[-4,-6]])/(-10)=[[2/5,3/5]]p_1=2/5 and p_2=3/5, where p_1 and p_2 represent the probabilities of player A's, using his strategies A_1 and A_2 respectively. Similarly, Player B's optimal strategies =([[1,1]] xx P_(Cof))/([[1,1]] xx P_(Adj) xx [[1],[1]])=([[1,1]][[2,-6],[-7,1]])/([[1,1]][[2,-7],[-6,1]][[1],[1]])=([[-5,-5]])/(-10)=[[1/2,1/2]]q_1=1/2 and q_2=1/2, where q_1 and q_2 represent the probabilities of player B's, using his strategies B_1 and B_2 respectively. Hence, Value of the game V = (Player A's optimal strategies) xx (Payoff matrix P_(ij)) xx (Player B's optimal strategies) V=[[2/5,3/5]][[1,7],[6,2]][[1/2],[1/2]]=4
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