def get_move(self, game_state: go.GameState):
"""Runs all playouts sequentially and returns the most visited action.
game_state: the current game state
Return: the selected action
"""
for _ in range(self._n_playout):
state_copy = game_state.copy()
self._playout(state_copy)
if self._root.is_leaf():
return PASS_MOVE
return max(self._root._children.items(),
key=lambda act_node: act_node[1]._n_visits)[0]
def get_move_probs(self, game_state: go.GameState):
"""Run all playouts sequentially and return the available actions and
their corresponding probabilities.
state: the current game state
temp: temperature parameter in (0, 1] controls the level of exploration
"""
for _ in range(self._n_playout):
state_copy = game_state.copy()
self._playout(state_copy)
if self._root.is_leaf():
return None, None
# calc the move probabilities based on visit counts at the root node
act_visits = [
(act, node._n_visits) for act, node in self._root._children.items()
]
acts, visits = zip(*act_visits)
act_probs = softmax(1.0 / self._temperature * np.log(np.array(visits) + 1e-10))
return acts, act_probs
