Using Domain-Configurable Search Control for Probabilistic Planning

Abstract

We describe how to improve the performance of MDP planning algorithms by modifying them to use the search-control mechanisms of planners such as TLPlan, SHOP2, and TALplanner. In our experiments, modified versions of RTDP, LRTDP, and Value Iteration were exponentially faster than the original algorithms. On the largest problems the original algorithms could solve, the modified ones were about 10,000 times faster. On another set of problems whose state spaces were more than 14,000 times larger than the original algorithms could solve, the modified algorithms took only about 1/3 second.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2005
Accession Number
ADA448062

Entities

People

  • Dana S. Nau
  • Ugur Kuter

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Autonomy
  • C4I

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Autonomous Navigation
  • Bayesian Networks
  • Computational Complexity
  • Computer Science
  • Control Systems
  • Dynamic Programming
  • Motion Planning
  • Navigation
  • Operations Research
  • Probability
  • Reasoning
  • Robot Navigation
  • Robots

Readers

  • Operations Research
  • Systems Analysis and Design

Technology Areas

  • Space
  • Space - Spacecraft Maneuvers