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Planning with Qualitative Action-Trajectory Constraints in PDDL

Title: Planning with Qualitative Action-Trajectory Constraints in PDDL
Authors: Bonassi L.; Gerevini A. E.; Scala E.
Contributors: Bonassi L.; Gerevini A. E.; Scala E.
Publisher Information: International Joint Conferences on Artificial Intelligence
Publication Year: 2022
Collection: Università degli Studi di Brescia: OPENBS - Open Archive UniBS
Description: In automated planning the ability of expressing constraints on the structure of the desired plans is important to deal with solution quality, as well as to express control knowledge. In PDDL3 this is supported through state-trajectory constraints corresponding to a class of LTLf formulae. In this paper, first we introduce a formalism to express trajectory constraints over actions in the plan, rather than over traversed states; the new class of constraints retains the same temporal modal operators of PDDL3, and adds two useful modalities. Then we investigate compilation-based methods to deal with action-trajectory constraints in propositional planning, and propose a new simple effective method. Finally, we experimentally study the usefulness of our action-trajectory constraints as a tool to express control knowledge. The experimental results show that the performance of a classical planner can be significantly improved by exploiting knowledge expressed by action constraints and handled by our compilation, while the same knowledge turns out to be less beneficial when specified as state constraints and handled by two state-of-the-art systems supporting state constraints.
Document Type: conference object
Language: English
Relation: info:eu-repo/semantics/altIdentifier/wos/WOS:001202342304102; ispartofbook:IJCAI International Joint Conference on Artificial Intelligence; 31st International Joint Conference on Artificial Intelligence, IJCAI 2022; firstpage:4606; lastpage:4613; numberofpages:8; journal:IJCAI; https://hdl.handle.net/11379/569805
Availability: https://hdl.handle.net/11379/569805
Rights: info:eu-repo/semantics/openAccess
Accession Number: edsbas.BC3C8E8F
Database: BASE