Planning with Partial Observability by SAT

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A4 Artikkeli konferenssijulkaisussa
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Date

2023

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Department of Computer Science

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Language

en

Pages

16
605-620

Series

Logics in Artificial Intelligence - 18th European Conference, JELIA 2023, Proceedings, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume 14281 LNAI

Abstract

Geffner & Geffner (2018) have shown that finding plans by reduction to SAT is not limited to classical planning, but is competitive also for fully observable non-deterministic planning. This work extends these ideas to planning with partial observability. Specifically, we handle partial observability by requiring that during the execution of a plan, the same actions have to be taken in all indistinguishable circumstances. We demonstrate that encoding this condition directly leads to far better scalability than an explicit encoding of observations-to-actions mapping, for high numbers of observations.

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Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

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DOI

10.1007/978-3-031-43619-2_41

Citation

Fadnis, S & Rintanen, J 2023, Planning with Partial Observability by SAT . in S Gaggl, M V Martinez, M Ortiz & M Ortiz (eds), Logics in Artificial Intelligence - 18th European Conference, JELIA 2023, Proceedings . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14281 LNAI, Springer, pp. 605-620, European Conference on Logics in Artificial Intelligence, Dresden, Germany, 20/09/2023 . https://doi.org/10.1007/978-3-031-43619-2_41

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https://urn.fi/URN:NBN:fi:aalto-202311086763

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[article-cris] Perustieteiden korkeakoulu / SCI