Scaling up planning by teasing out resource scheduling

Biplav Srivastava, Subbarao Kambhampati

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

12 Scopus citations


Planning consists of an action selection phase where actions are selected and ordered to reach the desired goals, and a resource alloca-tion 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 assign-ment 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 ig-nore 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 eficiency. We describe a prototype implementation of our approach on top of Graphplan and show impres-sive empirical results.

Original languageEnglish (US)
Title of host publicationRecent Advances in AI Planning - 5th European Conference on Planning, ECP 1999, Proceedings
EditorsSusanne Biundo, Maria Fox
PublisherSpringer Verlag
Number of pages15
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 Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
ISSN (Print)0302-9743


Other5th European Conference on Planning, ECP 1999
Country/TerritoryUnited Kingdom

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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