An Adaptive Clipping Approach for Proximal Policy Optimization

17 Apr 2018 Gang Chen Yiming Peng Mengjie Zhang

Very recently proximal policy optimization (PPO) algorithms have been proposed as first-order optimization methods for effective reinforcement learning. While PPO is inspired by the same learning theory that justifies trust region policy optimization (TRPO), PPO substantially simplifies algorithm design and improves data efficiency by performing multiple epochs of \emph{clipped policy optimization} from sampled data... (read more)

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METHOD TYPE
Entropy Regularization
Regularization
PPO
Policy Gradient Methods