Encoding Lifted Classical Planning in Propositional Logic

Authors

  • Daniel Höller Saarland University, Saarland Informatics Campus, Saarbrücken, Germany
  • Gregor Behnke University of Freiburg, Freiburg, Germany University of Amsterdam, ILLC, The Netherlands

Keywords:

Lifted Planning, Classical Planning, Planning As SAT

Abstract

Planning models are usually defined in lifted, i.e. first order formalisms, while most solvers need (variable-free) grounded representations. Though techniques for grounding prune unnecessary parts of the model, grounding might – nevertheless – be prohibitively expensive in terms of runtime. To overcome this issue, there has been renewed interest in solving planning problems based on the lifted representation in the last years. While these approaches are based on (heuristic) search, we present an encoding of lifted classical planning in propositional logic and use SAT solvers to solve it. Our evaluation shows that our approach is competitive with the heuristic search-based approaches in satisficing planning and outperforms them in a (length-)optimal setting.

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Published

2022-06-13

How to Cite

Höller, D., & Behnke, G. (2022). Encoding Lifted Classical Planning in Propositional Logic. Proceedings of the International Conference on Automated Planning and Scheduling, 32(1), 134-144. Retrieved from https://ojs.aaai.org/index.php/ICAPS/article/view/19794