Design and implementation of a replay framework based on a partial order planner

Laurie H. Ihrig, Subbarao Kambhampati

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

14 Scopus citations

Abstract

In this paper we describe the design and implementation of the derivation replay framework, DERSNLP+EBL (Derivational SNLP+EBL), which is based within a partial order planner. DERSNLP+EBL replays previous plan derivations by first repeating its earlier decisions in the context of the new problem situation, then extending the replayed path to obtain a complete solution for the new problem. When the replayed path cannot be extended into a new solution, explanation-based learning (EBL) techniques are employed to identify the features of the new problem which prevent this extension. These features are then added as censors on the retrieval of the stored case. To keep retrieval costs low, DERSNLP+EBL normally stores plan derivations for individual goals, and replays one or more of these derivations in solving multi-goal problems. Cases covering multiple goals are stored only when subplans for individual goals cannot be successfully merged. The aim in constructing the case library is to predict these goal interactions and to store a multi-goal case for each set of negatively interacting goals. We provide empirical results demonstrating the effectiveness of DERSNLP+EBL in improving planning performance on randomly-generated problems drawn from a complex domain.

Original languageEnglish (US)
Title of host publicationProceedings of the National Conference on Artificial Intelligence
Editors Anon
Place of PublicationMenlo Park, CA, United States
PublisherAAAI
Pages849-854
Number of pages6
Volume1
StatePublished - 1996
EventProceedings of the 1996 13th National Conference on Artificial Intelligence, AAAI 96. Part 1 (of 2) - Portland, OR, USA
Duration: Aug 4 1996Aug 8 1996

Other

OtherProceedings of the 1996 13th National Conference on Artificial Intelligence, AAAI 96. Part 1 (of 2)
CityPortland, OR, USA
Period8/4/968/8/96

ASJC Scopus subject areas

  • Software

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  • Cite this

    Ihrig, L. H., & Kambhampati, S. (1996). Design and implementation of a replay framework based on a partial order planner. In Anon (Ed.), Proceedings of the National Conference on Artificial Intelligence (Vol. 1, pp. 849-854). AAAI.