Policy Consolidation for Continual Reinforcement Learning

Christos Kaplanis
Christos Kaplanis

International Conference on Machine Learning, pp. 3242-3251, 2019.

Cited by: 8|Bibtex|Views6|Links
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Abstract:

We propose a method for tackling catastrophic forgetting in deep reinforcement learning that is \textit{agnostic} to the timescale of changes in the distribution of experiences, does not require knowledge of task boundaries, and can adapt in \textit{continuously} changing environments. In our \textit{policy consolidation} model, the pol...More

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