pastebin

import numpy as np

from scipy.optimize import linprog

 

payoff_player1 = np.array([[0, 25, 10],

                          [-25, 0, 5],

                          [-10, -5, 0]])

 

payoff_player2 = -payoff_player1.T

 

c_player1 = [-25, -10]

A_ub_player1 = [[-1, 0], [0, -1], [0, 0]]

b_ub_player1 = [-1, -1, 1]

bounds_player1 = [(0, 1), (0, 1)]

result_player1 = linprog(c_player1, A_ub=A_ub_player1, b_ub=b_ub_player1, bounds=bounds_player1)

 

optimal_strategy_player1 = result_player1.x

payoff_player1 = -result_player1.fun

 

c_player2 = [25, 10]

A_ub_player2 = [[1, 0], [0, 1], [0, 0]]

b_ub_player2 = [1, 1, -1]

bounds_player2 = [(0, 1), (0, 1)]

result_player2 = linprog(c_player2, A_ub=A_ub_player2, b_ub=b_ub_player2, bounds=bounds_player2)

 

optimal_strategy_player2 = result_player2.x

payoff_player2 = result_player2.fun

 

print("Optimal strategy for Player 1:", optimal_strategy_player1)

print("Payoff for Player 1:", payoff_player1)

print("Optimal strategy for Player 2:", optimal_strategy_player2)

print("Payoff for Player 2:", payoff_player2)