def test_action_and_result():
errors = {}
for state, example_result in action_and_result_examples.items():
problem = NQueensProblem(state=state)
result = [
problem.result(problem.initial, action)
for action in problem.actions(problem.initial)
]
if set(result) != set(example_result):
errors[state] = {
"example_result": example_result,
"result": result,
}
return errors
def time_function(problem, function):
problem2 = NQueensProblem(state=problem.random_state())
start = time.time()
results = function(problem2)
finish = time.time()
results["time"] = finish - start
return results
def generate_answers(hill_climbing_method, problems=None):
"""Return dictionary of results of running hill_climbing_method on problems."""
if problems is None:
examples = globals()[hill_climbing_method.__name__ + "_examples"]
answers = {}
for key in problems:
state, *args = key
problem = NQueensProblem(state=state)
random.seed(SEED)
result = hill_climbing_method(problem, *args)
answers[key] = result
return answers
num_exanded_nodes = []
solved = 0
for i in range(number):
results = time_function(problem, function)
times.append(results["time"])
num_exanded_nodes.append(results["expanded"])
if results["solved"]:
solved += 1
time_standard_deviation = numpy.std(times)
time_average = numpy.average(times)
expanded_standard_deviation = numpy.std(num_exanded_nodes)
expanded_average = numpy.average(num_exanded_nodes)
solving_probability = solved / number
print_and_write("expanded: {0:.5f} +- {1:.5f}".format(
expanded_average, expanded_standard_deviation))
print_and_write("time: {0:.5f} +- {1:.5f}".format(time_average,
time_standard_deviation))
print_and_write("solving_probability: " + str(solving_probability))
NUM_TRIALS = 100
NUM_QUEENS = 50
for i in range(1, NUM_QUEENS + 5):
print_and_write("N: " + str(i))
problem = NQueensProblem(N=i)
average_std(problem, hill_climbing_instrumented, NUM_TRIALS)
average_std(problem, hill_climbing_sideways, NUM_TRIALS)
average_std(problem, hill_climbing_random_restart, NUM_TRIALS)
print_and_write("")