The Laplacian in RL: Learning Representations with Efficient Approximations

international conference on learning representations, 2019.

Cited by: 10|Bibtex|Views70
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

The smallest eigenvectors of the graph Laplacian are well-known to provide a succinct representation of the geometry of a weighted graph. In reinforcement learning (RL), where the weighted graph may be interpreted as the state transition process induced by a behavior policy acting on the environment, approximating the eigenvectors of the ...More

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