Add DDPG #1
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brett-daley
requested changes
Mar 28, 2022
| with tf.GradientTape() as tape: | ||
| Q = self.predict_values(states, actions, network='main') | ||
| # TODO: Should we use huber loss here? | ||
| loss = tf.reduce_mean(huber_loss(targets - Q)) |
| Dense(1) | ||
| ]) | ||
| # We make one shared encoder for the actor and critic. | ||
| # TODO: Should we make separate main/target/exec encoders? |
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Yes, we should have target/exec models for the encoder, too.
| self.num_actions = self._vec_env.action_space.shape[-1] | ||
| self.action_limit = self._vec_env.action_space.high.max() | ||
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| actor_optimizer = Adam(lr=1e-4) |
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Let's have a single optimizer for actor + critic. Use Adam with lr=1e-4.
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