Combining macros and SAT planning

Vallati, Mauro (2010) Combining macros and SAT planning. In: Doctoral Consortium of the 11th Italian Association of Artificial Intelligence, 1st - 3rd December 2010, Brescia, Italy.

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Abstract

Planning based on propositional satisfiability is a powerful approach for computing makespan-optimal plans. However, it is usually slower then heuristic-based sub-optimal approaches. In this work we propose MacroSatPlan; a SatPlan based planner which exploits macros extracted by Macro-FF and uses a predictive model of the optimal solution length that is constructed by WEKA, a commonly used toolkit of machine learning algorithms.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Schools:	School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge School of Computing and Engineering
Depositing User:	Mauro Vallati
Date Deposited:	24 Oct 2012 15:39
Last Modified:	28 Aug 2021 20:27
URI:	https://eprints.hud.ac.uk/id/eprint/15367

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