Optimizing Information Bottleneck in Reinforcement Learning: A Stein Variational Approach

1 Jan 2021 Anonymous

The information bottleneck (IB) principle is an elegant and useful learning framework for extracting relevant information that an input feature contains about the target. The principle has been widely used in supervised and unsupervised learning... (read more)

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