Created
July 7, 2019 12:22
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| def act(self, state): | |
| if np.random.rand() <= self.epsilon: | |
| return enviroment.action_space.sample() | |
| q_values = self.q_network.predict(state) | |
| return np.argmax(q_values[0]) |
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