Planning with Partial Observability by SAT

Saurabh Fadnis*, Jussi Rintanen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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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.

Original languageEnglish
Title of host publicationLogics in Artificial Intelligence - 18th European Conference, JELIA 2023, Proceedings
EditorsSarah Gaggl, Maria Vanina Martinez, Magdalena Ortiz, Magdalena Ortiz
Number of pages16
ISBN (Print)978-3-031-43618-5
Publication statusPublished - 2023
MoE publication typeA4 Conference publication
EventEuropean Conference on Logics in Artificial Intelligence - Dresden, Germany
Duration: 20 Sept 202322 Sept 2023
Conference number: 18

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14281 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceEuropean Conference on Logics in Artificial Intelligence
Abbreviated titleJELIA


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