def compute_values():
payoff_matrix = PrisonersDilemmaPayoff()
delta = 0.9
mu = 0.0005
sim_time = time()
sim = simulate_payoff(AllC, AllC, payoff_matrix, delta, mistake_probability=mu, estimator_stdev=0.4)
sim_time = time() - sim_time
print("Simulated value = " + str(sim))
print("Time taken " + str(sim_time))
mult_sim_time = time()
mult_sim = mult_simulate_payoff(AllC, AllC, payoff_matrix, delta, mistake_probability=mu, estimator_stdev=0.4)
mult_sim_time = time() - mult_sim_time
print("Multiprocessed simulated value = " + str(mult_sim))
print("Time taken " + str(mult_sim_time))
calc_simple_time = time()
calc_simple = [0., 0.]
no_mistake = [0., 0.]
one_mistake = [0., 0.]
two_mistakes = [0., 0.]
for i in range(0, 100000):
for k in [0, 1]:
no_mistake[k] = ((1 - mu) ** 2) * (payoff_matrix.CC)[k]
two_mistakes[k] = (mu ** 2) * (payoff_matrix.DD)[k]
one_mistake[k] = (mu * (1 - mu)) * ((payoff_matrix.CD)[k] + (payoff_matrix.DC)[k])
calc_simple[k] += (delta ** i) * (no_mistake[k] + one_mistake[k] + two_mistakes[k])
calc_simple[0] *= (1 - delta)
calc_simple[1] *= (1 - delta)
calc_simple_time = time() - calc_simple_time
print("Calculated value (simplified) = " + str(calc_simple))
print("Time taken " + str(calc_simple_time))
calc_naive_time = time()
calc_naive = calculate_payoff_with_mistakes(AllC, AllC, payoff_matrix, delta, mu, 1e-5)
calc_naive_time = time() - calc_naive_time
print("Calculated value = " + str(calc_naive))
print("Time taken " + str(calc_naive_time))
mult_calc_naive_time = time()
mult_calc_naive = mult_calculate_payoff(AllC, AllC, payoff_matrix, delta, mu, 1e-5)
mult_calc_naive_time = time() - mult_calc_naive_time
print("Multiprocessed calculated value = " + str(mult_calc_naive))
print("Time taken " + str(mult_calc_naive_time))
expected_only_time = time()
expected_only_value = expected_only(AllC, AllC, payoff_matrix, delta, mu, 1e-5)
expected_only_time = time() - expected_only_time
print("Expected value only calculated value = " + str(expected_only_value))
print("Time taken " + str(expected_only_time))
def main():
"""
Iterate over combinations of strategies, continuation probability, mistake probability and epsilon, outputting
to a file
"""
continuation_values = [0.5, 0.6, 0.7, 0.8, 0.9]
mistake_values = [0.1, 0.01, 0.001, 0.0001, 0.00001]
epsilon_values = [1e-4, 1e-5, 1e-6]
# For all values of epsilon
for epsilon in epsilon_values:
# For all values of continuation prob
for continuation_probability in continuation_values:
# for all values of mistake prob
for mistake_probability in mistake_values:
# Open a file to write to
with open("results_" + str(epsilon) + "_" + str(continuation_probability) + "_" + str(mistake_probability), 'w') as file:
# Print the parameters for the run
print("Epsilon: " + str(epsilon), file=file)
print("Continuation prob: " + str(continuation_probability), file=file)
print("Mistake prob: " + str(mistake_probability), file=file)
# For each pair of strategies
for strategy_one in iter(strategy_list):
for strategy_two in iter(strategy_list):
# Compute the result
results = expected_only(strategy_one, strategy_two, PrisonersDilemmaPayoff(),
continuation_probability, mistake_probability, epsilon)
# Write the results to the file
print(str(strategy_one.__name__) + "," + str(strategy_two.__name__) + "," + str(results), file=file)
# When we're done with all the strategies, print done, just so I know how long things are taking
print("Done eps=" + str(epsilon) + " delta=" + str(continuation_probability) + " gamma=" + str(mistake_probability))