def play(θo, θm, θe, depth=TRAIN_DEPTH):
OPN, MID, END = 0, 1, 2
state = State()
first = np.random.choice([0, 1])
random_turns = 0 #np.random.choice([0] + [2]*2 + [4]*4 + [8]*8 + 16*[16] + 32*[32])
while (not state.terminal_test()):
print(f'Turn number {state.turn}')
print_board(state.board)
print()
if (state.turn + first) % 2:
if state.board[state.board > 0].sum() == 12:
θ = θo
elif state.board[state.board > 0].sum() > 5:
θ = θm
else:
θ = θe
state.history[state] += 1
if state.turn < random_turns:
num_actions = len(state.actions(False))
state = state.result(
state.actions(False)[np.random.choice(
[i for i in range(num_actions)])])
else:
searched_states = []
V = minimax(State(state.board), depth, θ, searched_states)
Δθ = np.zeros(num_features)
for s, vs, hs, features, d in searched_states:
#𝛿 = V(s) - H(features, θ)
𝛿 = vs - hs
Δθ += α * 𝛿 * features * λ**(depth - d)
for i in range(num_features):
if Δθ[i] > MAX_CHANGE:
Δθ[i] = MAX_CHANGE
elif Δθ[i] < -MAX_CHANGE:
Δθ[i] = -MAX_CHANGE
θ += Δθ
actions = []
actions2 = []
for a in state.actions():
child = state.result(a)
actions.append((-negamax(State(-1 * child.board), -INF,
INF, depth - 1, θ), a))
state = state.result(max(actions)[1])
else:
print(actions_with_indices(translate_actions(state.actions())))
i = int(input())
state = state.result(state.actions()[i])
state.board *= -1
state.turn += 1
print(state)
print('Game over!')
return θo, θm, θe
def H(features, θ):
h = np.dot(features, θ)
if h > 0.99*INF:
return 0.99*INF
if h < -0.99*INF:
return -0.99*INF
return h
α = 0.000001*3
λ = 0.5
MAX_CHANGE = 0.1
def tree_strap_train(θo, θm, θe, depth=TRAIN_DEPTH):
OPN, MID, END = 0, 1, 2
state = State()
random_turns = np.random.choice([0] + [2]*2 + [4]*4 + [8]*8 + 16*[16] + 32*[32])
while (not state.terminal_test()):
print(f'Turn number {state.turn}')
print(state)
print()
if state.board[state.board > 0].sum() == 12:
θ = θo
elif state.board[state.board > 0].sum() > 5:
θ = θm
else:
θ = θe
state.history[state] += 1
if state.turn < random_turns:
num_actions = len(state.actions(False))