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25 lines
1.0 KiB
Python
25 lines
1.0 KiB
Python
#######################################################################
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# Copyright (C) 2017 Shangtong Zhang(zhangshangtong.cpp@gmail.com) #
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# Permission given to modify the code as long as you keep this #
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# declaration at the top #
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#######################################################################
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import numpy as np
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class GreedyPolicy:
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def __init__(self, epsilon, end_episode, min_epsilon):
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self.init_epsilon = self.epsilon = epsilon
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self.current_episode = 0
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self.min_epsilon = min_epsilon
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self.end_episode = end_episode
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def sample(self, state):
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if np.random.rand() < self.epsilon:
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return np.random.randint(0, len(state))
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return np.argmax(state)
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def update_epsilon(self):
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self.epsilon = self.init_epsilon - float(self.current_episode) / self.end_episode * (self.init_epsilon - self.min_epsilon)
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self.epsilon = max(self.epsilon, self.min_epsilon)
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self.current_episode += 1
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