Isaza, Alejandro and Szepesvári, Csaba and Bulitko, Vadim and Greiner, Russel (2008) Speeding up planning in Markov decision processes via automatically constructed abstractions. In: UAI 2008. Proceedings of the 24th conference in uncertainty in artificial intelligence. Helsinki, 2008..

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Abstract

In this paper, we consider planning in stochastic shortest path problems, a subclass of Markov Decision Problems (MDP). We focus on medium-size problems whose state space can be fully enumerated. This problem has numerous important applications, such as navigation and planning under uncertainty. We propose a new approach for constructing a multi-level hierarchy of progressively simpler abstractions of the original problem. Once computed, the hierarchy can be used to speed up planning by first finding a policy for the most abstract level and then recursively refining it into a solution to the original problem. This approach is fully automated and delivers a speed-up of two orders of magnitude over a state-of-the-art MDP solver on sample problems while returning near-optimal solutions.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Depositing User:	Eszter Nagy
Date Deposited:	11 Dec 2012 15:32
Last Modified:	11 Dec 2012 15:32
URI:	https://eprints.sztaki.hu/id/eprint/5602

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