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arXiv · 1302.1573

Region-Based Approximations for Planning in Stochastic Domains

Nevin Lianwen Zhang·Wenju Liu
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Abstract

This paper is concerned with planning in stochastic domains by means of partially observable Markov decision processes (POMDPs). POMDPs are difficult to solve. This paper identifies a subclass of POMDPs called region observable POMDPs, which are easier to solve and can be used to approximate general POMDPs to arbitrary accuracy.

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Nevin Lianwen Zhang, Wenju Liu. 2013-02-06. Region-Based Approximations for Planning in Stochastic Domains. https://arxiv.org/abs/1302.1573

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