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Fixing Plans for PDDL+ Problems: Theoretical and Practical Implications

Title: Fixing Plans for PDDL+ Problems: Theoretical and Practical Implications
Authors: Percassi F.; Scala E.; Vallati M.
Contributors: Percassi F.; Scala E.; Vallati M.
Publisher Information: Association for the Advancement of Artificial Intelligence
Publication Year: 2023
Collection: Università degli Studi di Brescia: OPENBS - Open Archive UniBS
Description: The plan, execution, and replan framework has proven to be extremely valuable in complex real-world applications, where the dynamics of the environment cannot be fully encoded in the domain model. However, this comes at the cost of regenerating plans from scratch, which can be expensive when expressive formalisms like PDDL+ are used. Given the complexity of generating PDDL+ plans, it would be ideal to reuse as much as possible of an existing plan, rather than generating a new one from scratch every time. To support more effective exploitation of the plan, execution, and replan framework in PDDL+, in this paper, we introduce the problem of discretised PDDL+ plan fixing, which allows one to fix existing plans according to some defined constraints. We demonstrate the theoretical implications of the introduced notion and introduce reformulations to address the problem using domain-independent planning engines. Our results show that such reformulations can outperform replanning from scratch and unlock planning engines to solve more problems with fine-grained discretisations.
Document Type: conference object
Language: English
Relation: ispartofbook:Proceedings International Conference on Automated Planning and Scheduling, ICAPS; 33rd International Conference on Automated Planning and Scheduling, ICAPS 2023; volume:33; firstpage:324; lastpage:333; numberofpages:10; serie:PROCEEDINGS OF THE . INTERNATIONAL CONFERENCE ON AUTOMATED PLANNING AND SCHEDULING; https://hdl.handle.net/11379/584947
DOI: 10.1609/icaps.v33i1.27210
Availability: https://hdl.handle.net/11379/584947; https://doi.org/10.1609/icaps.v33i1.27210
Accession Number: edsbas.7AC6262C
Database: BASE