Scaling up planning by teasing out resource scheduling

Biplav Srivastava, Subbarao Kambhampati

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

Planning consists of an action selection phase where actions are selected and ordered to reach the desired goals, and a resource allocation phase where enough resources are assigned to ensure the successful execution of the chosen actions. In most real-world problems, these two phases are loosely coupled. Most existing planners do not exploit this loose-coupling, and perform both action selection and resource assignment employing the same algorithm. We shall show that this strategy severely curtails the scale-up potential of existing planners, including such recent ones as Graphplan and Blackbox. In response, we propose a novel planning framework in which resource allocation is teased apart from planning, and is handled in a separate "scheduling" phase. We ignore resource constraints during planning and produce an abstract plan that can correctly achieve the goals but for the resource constraints. Next, based on the actual resource availability, the abstract plan will be allocated resources to produce an executable plan. Our approach not only preserves both the correctness as well as the quality (measured in length) of the plan but also improves efficiency. We describe a prototype implementation of our approach on top of Graphplan and show impressive empirical results.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages172-186
Number of pages15
Volume1809
ISBN (Print)3540678662, 9783540678663
StatePublished - 2000
Event5th European Conference on Planning, ECP 1999 - Durham, United Kingdom
Duration: Sep 8 1999Sep 10 1999

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1809
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other5th European Conference on Planning, ECP 1999
CountryUnited Kingdom
CityDurham
Period9/8/999/10/99

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Srivastava, B., & Kambhampati, S. (2000). Scaling up planning by teasing out resource scheduling. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1809, pp. 172-186). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1809). Springer Verlag.