Optimizing plans through analysis of action dependencies and independencies

Lukáš Chrpa, Thomas Leo McCluskey, Hugh Osborne

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

10 Citations (Scopus)

Abstract

The problem of automated planning is known to be intractable in general. Moreover, it has been proven that in some cases finding an optimal solution is much harder than finding any solution. Existing techniques have to compromise between speed of the planning process and quality of solutions. For example, techniques based on greedy search often are able to obtain solutions quickly, but the quality of the solutions is usually low. Similarly, adding macro-operators to planning domains often enables planning speed-up, but solution sequences are typically longer. In this paper, we propose a method for optimizing plans with respect to their length, by post-planning analysis. The method is based on analyzing action dependencies and independencies by which we are able to identify redundant actions or non-optimal sub-plans. To evaluate the process we provide preliminary empirical evidence using benchmark domains.

Original languageEnglish
Title of host publicationICAPS 2012 - Proceedings of the 22nd International Conference on Automated Planning and Scheduling
Pages338-342
Number of pages5
Publication statusPublished - 2012
Event22nd International Conference on Automated Planning and Scheduling - Atibaia, Sao Paulo, Brazil
Duration: 25 Jun 201229 Jun 2012
Conference number: 22
http://icaps12.icaps-conference.org/ (Link to Conference Details)

Conference

Conference22nd International Conference on Automated Planning and Scheduling
Abbreviated titleICAPS 2012
CountryBrazil
CitySao Paulo
Period25/06/1229/06/12
Internet address

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  • Cite this

    Chrpa, L., McCluskey, T. L., & Osborne, H. (2012). Optimizing plans through analysis of action dependencies and independencies. In ICAPS 2012 - Proceedings of the 22nd International Conference on Automated Planning and Scheduling (pp. 338-342)