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RESEARCH ARTICLE   Open Access    

The RANTANPLAN planner: system description

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  • Abstract: RANTANPLAN is a numeric planning solver that takes advantage of recent advances in satisfiability modulo theories. It extends reduction to SAT approaches with an easy and efficient handling of numeric fluents using background theories. In this paper, we describe the design choices and features of RANTANPLAN, especially, how numeric reasoning is integrated in the system. We also provide experimental results showing that RANTANPLAN is competitive with existing exact numeric planners.
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  • Barrett C., Sebastiani R., Seshia S. & Tinelli C. 2009. Satisfiability modulo theories. In Handbook of Satisfiability, Biere, A., Heule, M., van Maaren, H. & Walsh, T. (eds). 185, Chapter 26. IOS Press, 825–885.

    Google Scholar

    Barták R. & Toropila D. 2010. Solving sequential planning problems via constraint satisfaction. Fundamenta Informaticae 99(2), 125–145.

    Google Scholar

    Belouaer L. & Maris F. 2012. SMT spatio-temporal planning. In ICAPS Workshop on Constraint Satisfaction Techniques for Planning and Scheduling Problems (COPLAS 2012), 6–15.

    Google Scholar

    Bofill M., Espasa J. & Villaret M. 2014. Efficient SMT encodings for the petrobras domain. In Proceedings of the 13th International Workshop on Constraint Modelling and Reformulation (ModRef 2014), 68–84.

    Google Scholar

    Bofill M., Espasa J. & Villaret M. 2016. A semantic notion of interference for planning modulo theories. In Proceedings of the Twenty-Sixth International Conference on Automated Planning and Scheduling, ICAPS 2016, 56–64.

    Google Scholar

    Dovier A., Formisano A. & Pontelli E. 2010. Multivalued action languages with constraints in CLP (FD). Theory and Practice of Logic Programming 10(2), 167–235.

    Google Scholar

    Dutertre B. & De Moura L. 2006. The Yices SMT solver. Technical report, Computer Science Laboratory, SRI International. http://yices.csl.sri.com.

    Google Scholar

    Fox M. & Long D. 2003. PDDL2.1: an extension to PDDL for expressing temporal planning domains. Journal of Artificial Intelligence Research 20, 61–124.

    Google Scholar

    Frisch A. M. & Giannaros P. A. 2010. SAT encodings of the at-most-fc constraint. Some old, some new, some fast, some slow. In 10th International Workshop on Constraint Modelling and Reformulation (ModRef 2010).

    Google Scholar

    Gerevini A. E., Saetti A. & Serina I. 2008. An approach to efficient planning with numerical fluents and multi-criteria plan quality. Artificial Intelligence 172(8), 899–944.

    Google Scholar

    Gregory P., Long D., Fox M. & Beck J. C. 2012. Planning modulo theories: extending the planning paradigm. In Twenty-Second International Conference on Automated Planning and Scheduling (ICAPS 2012). AAAI.

    Google Scholar

    Hoffmann J. 2003. The Metric-FF planning system: translating ‘ignoring delete lists’ to numeric state variables. Journal of Artificial Intelligence Research 20, 291–341.

    Google Scholar

    Hoffmann J., Gomes C. P., Selman B. & Kautz H. A. 2007. SAT encodings of state-space reachability problems in numeric domains. In 20th International Joint Conference on Artificial Intelligence (IJCAI 2007), 1918–1923.

    Google Scholar

    Kautz H. & Selman B. 1992. Planning as satisfiability. In 10th European Conference on Artificial Intelligence (ECAI 92), 359–363. John Wiley & Sons Inc.

    Google Scholar

    Kautz H. & Walser J. P. 1999. State-space planning by integer optimization. In AAAI/IAAI, 526–533.

    Google Scholar

    Kautz H. A., McAllester D. A. & Selman B. 1996. Encoding plans in propositional logic. In Fifth International Conference on Principles of Knowledge Representation and Reasoning (KR 96), 374–384.

    Google Scholar

    Rintanen J. 2012. Planning as satisfiability: heuristics. Artificial Intelligence 193, 45–86.

    Google Scholar

    Rintanen J., Heljanko K. & Niemelä I. 2006. Planning as satisfiability: parallel plans and algorithms for plan search. Artificial Intelligence 170(12–13), 1031–1080.

    Google Scholar

    Wolfman S. A. & Weld D. S. 1999. The LPSAT engine & its application to resource planning. In Sixteenth International Joint Conference on Artificial Intelligence (IJCAI 99), 310–317.

    Google Scholar

  • Cite this article

    Miquel Bofill, Joan Espasa, Mateu Villaret. 2016. The RANTANPLAN planner: system description. The Knowledge Engineering Review 31(5)452−464, doi: 10.1017/S0269888916000229
    Miquel Bofill, Joan Espasa, Mateu Villaret. 2016. The RANTANPLAN planner: system description. The Knowledge Engineering Review 31(5)452−464, doi: 10.1017/S0269888916000229

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RESEARCH ARTICLE   Open Access    

The RANTANPLAN planner: system description

The Knowledge Engineering Review  31 2016, 31(5): 452−464  |  Cite this article

Abstract: Abstract: RANTANPLAN is a numeric planning solver that takes advantage of recent advances in satisfiability modulo theories. It extends reduction to SAT approaches with an easy and efficient handling of numeric fluents using background theories. In this paper, we describe the design choices and features of RANTANPLAN, especially, how numeric reasoning is integrated in the system. We also provide experimental results showing that RANTANPLAN is competitive with existing exact numeric planners.

    • All authors supported by the Spanish Ministry of Economy and Competitiveness through project HeLo (ref. TIN2012-33042) and project LoCoS (ref. TIN2015-66293-R) and by Universitat de Girona (UdG) through grant MPCUdG2016/055.

    • By a ground action 〈p, e〉 we refer to an action where p and e are built on the state variables that result from grounding a PDDL model, as explained above.

    • A full work devoted to this interference notion is currently submitted for publication.

    • © Cambridge University Press, 2016 2016Cambridge University Press
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    Cite this article
    Miquel Bofill, Joan Espasa, Mateu Villaret. 2016. The RANTANPLAN planner: system description. The Knowledge Engineering Review 31(5)452−464, doi: 10.1017/S0269888916000229
    Miquel Bofill, Joan Espasa, Mateu Villaret. 2016. The RANTANPLAN planner: system description. The Knowledge Engineering Review 31(5)452−464, doi: 10.1017/S0269888916000229
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