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arXiv · 1207.1386

Metrics for Markov Decision Processes with Infinite State Spaces

Norman Ferns·Prakash Panangaden·Doina Precup
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Abstract

We present metrics for measuring state similarity in Markov decision processes (MDPs) with infinitely many states, including MDPs with continuous state spaces. Such metrics provide a stable quantitative analogue of the notion of bisimulation for MDPs, and are suitable for use in MDP approximation. We show that the optimal value function associated with a discounted infinite horizon planning task varies continuously with respect to our metric distances.

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Norman Ferns, Prakash Panangaden, Doina Precup. 2012-07-04. Metrics for Markov Decision Processes with Infinite State Spaces. https://arxiv.org/abs/1207.1386

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