Exploiting block deordering for improving planners efficiency

Lukaš Chrpa, Fazlul Hasan Siddiqui

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

4 Citations (Scopus)

Abstract

Capturing and exploiting structural knowledge of planning problems has shown to be a successful strategy for making the planning process more efficient. Plans can be decomposed into its constituent coherent subplans, called blocks, that encapsulate some effects and preconditions, reducing interference and thus allowing more deordering of plans. According to the nature of blocks, they can be straightforwardly transformed into useful macro-operators (shortly, "macros"). Macros are well known and widely studied kind of structural knowledge because they can be easily encoded in the domain model and thus exploited by standard planning engines. In this paper, we introduce a method, called BLOMA, that learns domain-specific macros from plans, decomposed into "macro-blocks" which are extensions of blocks, utilising structural knowledge they capture. In contrast to existing macro learning techniques, macro-blocks are often able to capture high-level activities that form a basis for useful longer macros (i.e. those consisting of more original operators). Our method is evaluated by using the IPC benchmarks with state-of-the-art planning engines, and shows considerable improvement in many cases.

Original languageEnglish
Title of host publicationIJCAI 2015 - Proceedings of the 24th International Joint Conference on Artificial Intelligence
PublisherInternational Joint Conferences on Artificial Intelligence
Pages1537-1543
Number of pages7
Volume2015-January
ISBN (Electronic)9781577357384
Publication statusPublished - 2015
Event24th International Joint Conference on Artificial Intelligence - Buenos Aires, Argentina
Duration: 25 Jul 201531 Jul 2015
Conference number: 24
http://www.ijcai.org/past_conferences (Link to Conference Website )

Conference

Conference24th International Joint Conference on Artificial Intelligence
Abbreviated titleIJCAI 2015
CountryArgentina
CityBuenos Aires
Period25/07/1531/07/15
Internet address

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Macros
Planning
Engines

Cite this

Chrpa, L., & Siddiqui, F. H. (2015). Exploiting block deordering for improving planners efficiency. In IJCAI 2015 - Proceedings of the 24th International Joint Conference on Artificial Intelligence (Vol. 2015-January, pp. 1537-1543). International Joint Conferences on Artificial Intelligence.
Chrpa, Lukaš ; Siddiqui, Fazlul Hasan. / Exploiting block deordering for improving planners efficiency. IJCAI 2015 - Proceedings of the 24th International Joint Conference on Artificial Intelligence. Vol. 2015-January International Joint Conferences on Artificial Intelligence, 2015. pp. 1537-1543
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Chrpa, L & Siddiqui, FH 2015, Exploiting block deordering for improving planners efficiency. in IJCAI 2015 - Proceedings of the 24th International Joint Conference on Artificial Intelligence. vol. 2015-January, International Joint Conferences on Artificial Intelligence, pp. 1537-1543, 24th International Joint Conference on Artificial Intelligence, Buenos Aires, Argentina, 25/07/15.

Exploiting block deordering for improving planners efficiency. / Chrpa, Lukaš; Siddiqui, Fazlul Hasan.

IJCAI 2015 - Proceedings of the 24th International Joint Conference on Artificial Intelligence. Vol. 2015-January International Joint Conferences on Artificial Intelligence, 2015. p. 1537-1543.

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

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Chrpa L, Siddiqui FH. Exploiting block deordering for improving planners efficiency. In IJCAI 2015 - Proceedings of the 24th International Joint Conference on Artificial Intelligence. Vol. 2015-January. International Joint Conferences on Artificial Intelligence. 2015. p. 1537-1543