Exact decomposition approaches for Markov decision processes: A survey

Exact decomposition approaches for Markov decision processes: A survey

0.00 Avg rating0 Votes
Article ID: iaor20105661
Volume: 2010
Issue: 7
Start Page Number: 701
End Page Number: 710
Publication Date: Jul 2010
Journal: Advances in Operations Research
Authors: , ,
Keywords: decision theory
Abstract:

As classical methods are intractable for solving Markov decision processes(MDPs) requiring a large state space, decomposition and aggregation techniques are very useful to cope with large problems. These techniques are in general a special case of the classic Divide-and-Conquer framework to split a large, unwieldy problem into smaller components and solving the parts in order to construct the global solution. This paper reviews most of decomposition approaches encountered in the associated literature over the past two decades, weighing their pros and cons. We consider several categories of MDPs (average, discounted, and weighted MDPs), and we present briefly a variety of methodologies to find or approximate optimal strategies.

Reviews

Required fields are marked *. Your email address will not be published.