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Conditional effects in numeric planning reloaded

Title: Conditional effects in numeric planning reloaded
Authors: Bonassi, L; Espasa Arxer, J; Percassi, F; Scala, E
Publisher Information: IOS Press
Publication Year: 2025
Collection: Oxford University Research Archive (ORA)
Description: Automated planning, a core area of artificial intelligence, aims to generate action sequences that achieve specified goals based on a formal model. In classical planning, where only Boolean state variables are allowed, conditional effects are the standard approach for modelling actions with state-dependent outcomes. However, unlike in the classical setting, relatively little research has focused on developing planning methods for numeric problems with conditional effects. To address this gap in the literature, this work studies numeric planning with conditional effects. We formalise its semantics and revise existing classical planning compilations for conditional effects to account for the specific features of numeric planning. This results in three encodings: two are designed for the full class of numeric planning problems, while the third is specific to tasks with conditional effects that increase or decrease variables by a constant, transforming such problems into instances of Simple Numeric Planning, a well-known and practically significant subclass of numeric tasks. The experimental evaluation compares these compilations across both newly designed and compelling benchmarks as well as existing domains featuring conditional effects. Our empirical findings reveal complementary behaviour among the approaches, highlighting the practical impact of selecting the appropriate compilation for different problem structures.
Document Type: conference object
Language: English
Relation: https://doi.org/10.3233/FAIA251404
DOI: 10.3233/FAIA251404
Availability: https://doi.org/10.3233/FAIA251404; https://ora.ox.ac.uk/objects/uuid:182c6a9d-c236-4e6a-8e7c-4fd684e2caf9
Rights: info:eu-repo/semantics/openAccess ; CC Attribution-NonCommercial (CC BY-NC)
Accession Number: edsbas.18706F6B
Database: BASE