Monte Carlo tree search

class srl.algorithms.mcts.Config(observation_mode: Union[str, srl.base.define.ObservationModes] = <ObservationModes.ENV: 1>, override_observation_type: srl.base.define.SpaceTypes = <SpaceTypes.UNKNOWN: 0>, override_action_type: Union[str, srl.base.define.RLBaseActTypes] = <RLBaseActTypes.NONE: 1>, action_division_num: int = 10, observation_division_num: int = 1000, frameskip: int = 0, extend_worker: Optional[Type[ForwardRef('ExtendWorker')]] = None, parameter_path: str = '', memory_path: str = '', use_rl_processor: bool = True, processors: List[ForwardRef('RLProcessor')] = <factory>, render_image_processors: List[ForwardRef('RLProcessor')] = <factory>, enable_state_encode: bool = True, enable_action_decode: bool = True, enable_reward_encode: bool = True, enable_done_encode: bool = True, window_length: int = 1, render_image_window_length: int = 1, enable_sanitize: bool = True, enable_assertion: bool = False, num_simulations: int = 10, expansion_threshold: int = 5, discount: float = 1.0, uct_c: float = np.float64(1.4142135623730951))

num_simulations: int = 10

シミュレーション回数

expansion_threshold: int = 5

展開の閾値

discount: float = 1.0

割引率

uct_c: float = np.float64(1.4142135623730951)

UCT C