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Applied Deep Learning (2019 Spring) @ NTU

Python 42.66% Jupyter Notebook 57.34%
adl2019spring ntu adl gan generative-adversarial-network reinforcement-learning policy-gradient deep-q-learning-network actor-critic image-generation

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airob zhangyuanxun tommyvsfu1 milorin markhsia samuel1043

adl2019's Issues

PPO squared-error loss

想請問下PPO value loss的計算方法，因為PPO paper上好像沒定義很清楚squared-error loss的計算( 有點不太能理解？)

我發現你在 ADL, MLDS 兩邊的PPO squared-error loss 計算方式不大一樣，然後我看了網路上很多寫法(tensorlayer等等）也都不大相同，想請問下這方便你是怎麼理解的？謝謝

ADL hw3 (agent_pg.py)
loss = -torch.min(surr1, surr2) + 1.0 * nn.MSELoss()(state_values, rewards)- 0.01 * entropy

MLDS hw4 (agent_pg.py)
loss_vf = tf.squared_difference(self.rewards + self.gamma * self.v_preds_next, v_preds)

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