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Authors: Dominik Schreiber 1 ; Damien Pellier 2 ; Humbert Fiorino 2 and Tomáš Balyo 3

Affiliations: 1 Karlsruhe Institut für Technologie, Karlsruhe, Germany, Université Grenoble-Alpes, Grenoble and France ; 2 Université Grenoble-Alpes, Grenoble and France ; 3 Karlsruhe Institut für Technologie, Karlsruhe and Germany

ISBN: 978-989-758-350-6

Keyword(s): HTN Planning, SAT Planning, Incremental SAT Solving.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Formal Methods ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Planning and Scheduling ; Simulation and Modeling ; Symbolic Systems ; Task Planning and Execution

Abstract: Hierarchical Task Networks (HTN) are one of the most expressive representations for automated planning problems. On the other hand, in recent years, the performance of SAT solvers has been drastically improved. To take advantage of these advances, we investigate how to encode HTN problems as SAT problems. In this paper, we propose two new encodings: GCT (Grammar-Constrained Tasks) and SMS (Stack Machine Simulation), which, contrary to previous encodings, address recursive task relationships in HTN problems. We evaluate both encodings on benchmark domains from the International Planning Competition (IPC), setting a new baseline in SAT planning on modern HTN domains.

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Paper citation in several formats:
Schreiber, D.; Pellier, D.; Fiorino, H. and Balyo, T. (2019). Efficient SAT Encodings for Hierarchical Planning.In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-350-6, pages 531-538. DOI: 10.5220/0007343305310538

@conference{icaart19,
author={Dominik Schreiber. and Damien Pellier. and Humbert Fiorino. and Tomáš Balyo.},
title={Efficient SAT Encodings for Hierarchical Planning},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2019},
pages={531-538},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007343305310538},
isbn={978-989-758-350-6},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Efficient SAT Encodings for Hierarchical Planning
SN - 978-989-758-350-6
AU - Schreiber, D.
AU - Pellier, D.
AU - Fiorino, H.
AU - Balyo, T.
PY - 2019
SP - 531
EP - 538
DO - 10.5220/0007343305310538

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