def greedy_iterations_maxchild(
iterations: int = 100,
exploration_weight: float = 0.0) -> 'MonteCarloTreeSearch':
stop_cond = IterationsStoppingCondition(iterations=iterations)
select_crit = MaxChild()
return GreedyMCTS(stopping_condition=stop_cond,
selection_criteria=select_crit)
def uct_iterations_maxchild_random_expansion(
iterations: int = 100,
exploration_weight: float = 0.5) -> 'MonteCarloTreeSearch':
stop_cond = IterationsStoppingCondition(iterations=iterations)
select_crit = MaxChild()
return UCTRandomExpansion(stopping_condition=stop_cond,
selection_criteria=select_crit,
exploration_weight=exploration_weight)
def uct_anytime_maxchild_random_expansion(
seconds: int = 1,
exploration_weight: float = 0.5) -> 'MonteCarloTreeSearch':
stop_cond = AnytimeStoppingCondition(seconds=seconds)
select_crit = MaxChild()
return UCTRandomExpansion(stopping_condition=stop_cond,
selection_criteria=select_crit,
exploration_weight=exploration_weight)
def montecarlo_iterations_maxchild(
iterations: int = 100) -> 'MonteCarloBasic':
stop_cond = IterationsStoppingCondition(iterations=iterations)
select_crit = MaxChild()
return MonteCarloBasic(stopping_condition=stop_cond,
selection_criteria=select_crit)
def montecarlo_anytime_maxchild(seconds: int = 1) -> 'MonteCarloBasic':
stop_cond = AnytimeStoppingCondition(seconds=seconds)
select_crit = MaxChild()
return MonteCarloBasic(stopping_condition=stop_cond,
selection_criteria=select_crit)