def run_sim(controller=player_0(normalize=True),
enemy=1,
npop=50,
ngens=10,
m0=.07,
m1=.1,
m2=.07,
m3=.07,
m4=.07,
highf_r=1.,
lowf_r=.33,
n_hidden=None,
keep_elite=True):
generations = {}
for gen in range(ngens):
print(" - - - - GENERATION %s - - - - " % gen)
if gen == 0:
pop = [{
"bias": np.random.randn(1, 5),
"weights": np.random.randn(20, 5),
"ID": _,
"parents": _
} for _ in range(npop)]
pop = test_pop(pop, enemy)
generations[gen] = pop
else:
new_pop = reproduce(generations[gen - 1], highf_r, lowf_r, m0, m1,
m2, m3, m4, keep_elite)
new_pop = test_pop(new_pop, enemy)
generations[gen] = new_pop
FF = []
for gen in generations:
pop = generations[gen]
pop_fitness = [_["fitness"] for _ in pop]
FF.append(pop_fitness)
df = pd.DataFrame(FF).T
result = {
"data": df,
"meta": {
"npop": npop,
"ngens": ngens,
"m3": m3,
"m4": m4,
"m0": m0,
"m1": m1,
"m2": m2,
"highf_r": highf_r,
"lowf_r": lowf_r,
"n_hidden": n_hidden,
"elite": keep_elite,
"enemy": enemy
}
}
with open(str(datetime.datetime.now()), "wb") as f:
pickle.dump(result, f)
return df
def run(genes, norm_inputs, en=1):
env = Environment(experiment_name=experiment_name,
playermode="ai",
player_controller=player_0(normalize=norm_inputs),
speed="fastest",
enemymode="static",
level=2,
randomini="no",
enemies=[en])
return env.play(genes)
# results = []
# for e in [1,2,3,4,5,6,7,8]:
# df = run_sim(controller=player_0(normalize=True),
# enemy=e,
# npop=100,
# ngens=20,
# m0=.12,
# m1=.2,
# m2=.12,
# m3=.15,
# m4=.12,
# highf_r = 1.,
# lowf_r = .05,
# n_hidden=None,
# keep_elite=True
# )
res = run_sim(controller=player_0(normalize=True),
enemy=1,
npop=100,
ngens=15,
m0=.05,
m1=.125,
m2=.05,
m3=.05,
m4=.05,
highf_r=1.,
lowf_r=.05,
n_hidden=None,
keep_elite=True)
