Meta-SAC Alternatives
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pytorch-a2c-ppo-acktr-gail
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
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Meta-SAC reviews and mentions
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Do policy gradient methods also require some mechanism for exploration?
A simple approach that can help is a linear entropy schedule: Start at a high value to explore early, decay over time to learn a more optimal policy. Some variants of SAC autotune the entropy over time. A more advanced approach is AGAC, which does something like a GAN to encourage the PPO/A2C policy to explore by forcing it to be less predictable. There are many approaches, these are just a sample
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twni2016/Meta-SAC is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of Meta-SAC is Python.
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