The Laplacian in RL: Learning Representations with Efficient Approximations
international conference on learning representations, 2019.
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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