Learning Representations in Reinforcement Learning:An Information Bottleneck Approach

12 Nov 2019 Pei Yingjun Hou Xinwen

The information bottleneck principle is an elegant and useful approach to representation learning. In this paper, we investigate the problem of representation learning in the context of reinforcement learning using the information bottleneck framework, aiming at improving the sample efficiency of the learning algorithms... (read more)

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METHOD TYPE
Entropy Regularization
Regularization
A2C
Policy Gradient Methods
PPO
Policy Gradient Methods