Created
July 20, 2019 10:34
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| def act(self, frame): | |
| if np.random.rand() <= self.epsilon: | |
| return self.enviroment.action_space.sample() | |
| frame = np.expand_dims(np.asarray(frame).astype(np.float64), axis=0) | |
| q_values = self.q_network.predict(frame) | |
| return np.argmax(q_values[0]) |
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