Generating macro-operators by exploiting inner entanglements

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

2 Citations (Scopus)

Abstract

In Automated Planning, learning and exploiting additional knowledge within a domain model, in order to improve plan generation speed-up and increase the scope of problems solved, has attracted much research. Reformulation techniques such as those based on macro-operators or entanglements are very promising because they are to some extent domain model and planning engine independent. This paper aims to exploit recent work on inner entanglements, relations between pairs of planning operators and predicates encapsulating exclusivity of predicate 'achievements' or 'requirements', for generating macro-operators.We discuss conditions which are necessary for generating such macro-operators and conditions that allow removing primitive operators without compromising solvability of a given (class of) problem(s). The effectiveness of our approach will be experimentally shown on a set of well-known benchmark domains using several highperforming planning engines.

Original languageEnglish
Title of host publicationProceedings of the 10th Symposium on Abstraction, Reformulation, and Approximation, SARA 2013
Pages42-49
Number of pages8
Publication statusPublished - 2013
Event10th Symposium on Abstraction, Reformulation, and Approximation - Leavenworth, United States
Duration: 11 Jul 201312 Jul 2013
https://www.aaai.org/ocs/index.php/SARA/SARA13 (Link to Symposium Details )

Conference

Conference10th Symposium on Abstraction, Reformulation, and Approximation
Abbreviated titleSARA 2013
CountryUnited States
CityLeavenworth
Period11/07/1312/07/13
Internet address

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  • Cite this

    Chrpa, L., Vallati, M., McCluskey, T. L., & Kitchin, D. (2013). Generating macro-operators by exploiting inner entanglements. In Proceedings of the 10th Symposium on Abstraction, Reformulation, and Approximation, SARA 2013 (pp. 42-49)