Soft Actor-Critic (Autotuned Temperature)
Soft Actor-Critic (Autotuned Temperature)
**Soft Actor Critic (Autotuned Temperature** is a modification of the [SAC](https://paperswithcode.com/method/soft-actor-critic) reinforcement learning algorithm. [SAC](https://paperswithcode.com/method/sac) can suffer from brittleness to the temperature hyperparameter. Unlike in conventional reinforcement learning, where the optimal policy is independent of scaling of the reward function, in maximum entropy reinforcement learning the scaling factor has to be compensated by the choice a of suitable temperature, and a sub-optimal temperature can drastically degrade performance. To resolve this issue, SAC with Autotuned Temperature has an automatic gradient-based temperature tuning method that adjusts the expected entropy over the visited states to match a target value.
Soft Actor-Critic Algorithms and Applications
https://paperswithcode.com/paper/soft-actor-critic-algorithms-and-applications
Soft Actor-Critic Algorithms and Applications