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arXiv · 1110.2736

Marvin: A Heuristic Search Planner with Online Macro-Action Learning

A. I. Coles·A. J. Smith
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Abstract

This paper describes Marvin, a planner that competed in the Fourth International Planning Competition (IPC 4). Marvin uses action-sequence-memoisation techniques to generate macro-actions, which are then used during search for a solution plan. We provide an overview of its architecture and search behaviour, detailing the algorithms used. We also empirically demonstrate the effectiveness of its features in various planning domains; in particular, the effects on performance due to the use of macro-actions, the novel features of its search behaviour, and the native support of ADL and Derived Predicates.

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BibTeXRIS

A. I. Coles, A. J. Smith. 2011-10-12. Marvin: A Heuristic Search Planner with Online Macro-Action Learning. https://doi.org/10.1613/jair.2077

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