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arXiv · 1404.3328

Myopic Bounds for Optimal Policy of POMDPs: An extension of Lovejoy's structural results

Vikram Krishnamurthy·Udit Pareek
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Abstract

This paper provides a relaxation of the sufficient conditions, and also an extension of the structural results for Partially Observed Markov Decision Processes (POMDPs) given in Lovejoy (1987). Sufficient conditions are provided so that the optimal policy can be upper and lower bounded by judiciously chosen myopic policies. These myopic policy bounds are constructed to maximize the volume of belief states where they coincide with the optimal policy. Numerical examples illustrate these myopic bounds for both continuous and discrete observation sets.

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BibTeXRIS

Vikram Krishnamurthy, Udit Pareek. 2015-11-14. Myopic Bounds for Optimal Policy of POMDPs: An extension of Lovejoy's structural results. https://arxiv.org/abs/1404.3328

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