On Planning with Qualitative State-Trajectory Constraints in PDDL3 by Compiling them Away

Luigi Bonassi, Alfonso Emilio Gerevini, Francesco Percassi, Enrico Scala

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

Abstract

We tackle the problem of classical planning with qualitative state-trajectory constraints as those that can be expressed in PDDL3. These kinds of constraints allow a user to formally specify which temporal properties a plan has to conform with through a class of LTL formulae. We study a compilationbased approach that, without resorting to automata for representing and dealing with such properties, takes a PDDL3 problem and generates a classical planning problem with conditional effects that is solvable iff so is the PDDL3 problem. Our compilation exploits a regression operator to revise the actions’ preconditions and conditional effects in a way to (i) prohibit executions that irreversibly violate temporal constraints (ii) be sensitive to executions that traverse those necessary subgoals implied by the temporal specification. An experimental analysis shows that our approach performs better than other state-of-the-art approaches over the majority of the considered benchmark domains.
Original languageEnglish
Title of host publicationProceedings of the 31st International Conference on Automated Planning and Scheduling
Subtitle of host publicationICAPS 2021
EditorsSusanne Biundo, Minh Do, Robert Goldman, Michael Katz, Qiang Yang, Hankz Hankui Zhou
PublisherAAAI press
Pages46-50
Number of pages5
Volume31
ISBN (Print)9781577358671
DOIs
Publication statusPublished - 17 May 2021
Event31st International Conference on Automated Planning and Scheduling - Now to be held online due to COVID-19), Virtual from Guangzhou, China
Duration: 2 Aug 202113 Aug 2021
Conference number: 31
https://icaps21.icaps-conference.org/

Publication series

NameProceedings of the International Conference on Automated Planning and Scheduling
PublisherAAAI Press
Volume31
ISSN (Print)2334-0835
ISSN (Electronic)2334-0843

Conference

Conference31st International Conference on Automated Planning and Scheduling
Abbreviated titleICAPS 2021
CountryChina
CityVirtual from Guangzhou
Period2/08/2113/08/21
Internet address

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