An Effective Polynomial Technique for Compiling Conditional Effects Away

Alfonso Emilio Gerevini, Francesco Percassi, Enrico Scala

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

1 Citation (Scopus)

Abstract

The paper introduces a novel polynomial compilation technique for the sound and complete removal of conditional effects in classical planning problems. Similar to Nebel's polynomial compilation of conditional effects, our solution also decomposes each action with conditional effects into several simpler actions. However, it does so more effectively by exploiting the actual structure of the given conditional effects. We characterise such a structure using a directed graph and leverage it to significantly reduce the number of additional atoms required, thereby shortening the size of valid plans. Our experimental analysis indicates that this approach enables the effective use of polynomial compilations, offering benefits in terms of modularity and reusability of existing planners. It also demonstrates that a compilation-based approach can be more efficient, either independently or in synergy with state-of-the-art optimal planners that directly support conditional effects.
Original languageEnglish
Title of host publicationProceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence
Subtitle of host publicationThirty-Sixth Conference on Innovative Applications of Artificial Intelligence: Fourteenth Symposium on Educational Advances in Artificial Intelligence
EditorsMichael Wooldridge, Jennifer Dy, Sriraam Natarajan
PublisherAAAI press
Pages20104-20112
Number of pages9
Volume38
Edition18
ISBN (Print)1577358872, 9781577358879
DOIs
Publication statusPublished - 25 Mar 2024
Event38th Annual AAAI Conference on Artificial Intelligence - Vancouver Convention Centre – West Building, Vancouver, Canada
Duration: 20 Feb 202427 Feb 2024
Conference number: 38
https://aaai.org/aaai-conference/

Publication series

NameProceedings of the AAAI Conference on Artificial Intelligence
PublisherAAAI
Number18
Volume38
ISSN (Print)2159-5399
ISSN (Electronic)2374-3468

Conference

Conference38th Annual AAAI Conference on Artificial Intelligence
Abbreviated titleAAAI-24
Country/TerritoryCanada
CityVancouver
Period20/02/2427/02/24
Internet address

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