Applying integer programming to AI planning

  • Authors:

  • Thomas Vossen;Michael Ball;Amnon Lotem;Dana Nau

  • Affiliations:

  • Robert H. Smith School of Business and Institute for Systems Research, Email: mball@rhsmith.umd.edu, tvossen@rhsmith.umd.edu;Robert H. Smith School of Business and Institute for Systems Research, Email: mball@rhsmith.umd.edu, tvossen@rhsmith.umd.edu;Department of Computer Science and Institute for Systems Research, University of Maryland, College Park, MD 20742, USA, Email: nau@cs.umd.edu, lotem@cs.umd.edu;Department of Computer Science and Institute for Systems Research, University of Maryland, College Park, MD 20742, USA, Email: nau@cs.umd.edu, lotem@cs.umd.edu

  • Venue:
  • The Knowledge Engineering Review
  • Year:
  • 2000

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Abstract

Despite the historical difference in focus between AI planning techniques and Integer Programming (IP) techniques, recent research has shown that IP techniques show significant promise in their ability to solve AI planning problems. This paper provides approaches to encode AI planning problems as IP problems, describes some of the more significant issues that arise in using IP for AI planning, and discusses promising directions for future research.