An improved grid-based approximation algorithm for POMDPs

  • Authors:

  • Rong Zhou;Eric A. Hansen

  • Affiliations:

  • Computer Science Department, Mississippi State University, MS;Computer Science Department, Mississippi State University, MS

  • Venue:
  • IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
  • Year:
  • 2001

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Abstract

Although a partially observable Markov decision process (POMDP) provides an appealing model for problems of planning under uncertainty, exact algorithms for POMDPs are intractable. This motivates work on approximation algorithms, and grid-based approximation is a widely-used approach. We describe a novel approach to grid-based approximation that uses a variable-resolution regular grid, and show that it outperforms previous grid-based approaches to approximation.