Add dirichlet noise to root prior and add uniform noise to initial Q value
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@ -26,7 +26,7 @@ class MCTSNode(object):
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class UCTNode(MCTSNode):
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class UCTNode(MCTSNode):
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def __init__(self, parent, action, state, action_num, prior, mcts, inverse=False):
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def __init__(self, parent, action, state, action_num, prior, mcts, inverse=False):
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super(UCTNode, self).__init__(parent, action, state, action_num, prior, inverse)
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super(UCTNode, self).__init__(parent, action, state, action_num, prior, inverse)
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self.Q = np.zeros([action_num])
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self.Q = np.random.uniform(-1, 1, action_num) * (1e-6)
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self.W = np.zeros([action_num])
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self.W = np.zeros([action_num])
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self.N = np.zeros([action_num])
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self.N = np.zeros([action_num])
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self.c_puct = c_puct
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self.c_puct = c_puct
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@ -121,12 +121,14 @@ class ActionNode(object):
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class MCTS(object):
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class MCTS(object):
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def __init__(self, simulator, evaluator, start_state, action_num, method="UCT",
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def __init__(self, simulator, evaluator, start_state, action_num, method="UCT",
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role="unknown", debug=False, inverse=False):
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role="unknown", debug=False, inverse=False, epsilon=0.25):
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self.simulator = simulator
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self.simulator = simulator
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self.evaluator = evaluator
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self.evaluator = evaluator
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self.role = role
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self.role = role
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self.debug = debug
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self.debug = debug
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self.epsilon = epsilon
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prior, _ = self.evaluator(start_state)
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prior, _ = self.evaluator(start_state)
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prior = (1 - self.epsilon) * prior + self.epsilon * np.random.dirichlet(1.0/action_num * np.ones([action_num]))
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self.action_num = action_num
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self.action_num = action_num
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if method == "":
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if method == "":
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self.root = start_state
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self.root = start_state
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