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Learning More Expressive General Policies for Classical Planning Domains
; ;
2025
Online
DOI: 10.48550/arXiv.2403.11734
Einrichtungen
- Lehrstuhl für Maschinelles Lernen und Inferenz (Informatik 6) (122010)
- Fachgruppe Informatik (120000)
Projekte
- AvH 1228833 - ESP - AHP-KI - Alexander von Humboldt-Professur für Künstliche Intelligenz (1228833 - ESP - AHP-KI) (1228833 - ESP - AHP-KI)
- RLeap - From Data-based to Model-based AI: Representation Learning for Planning (885107) (885107)
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Dokumenttyp
Preprint
Format
online
Sprache
English
Externe Identnummern
arXiv: arXiv:2403.11734
OpenAlex: W4392970256
Interne Identnummern
RWTH-2025-02460
Datensatz-ID: 1006385
Related:
Contribution to a book/Contribution to a conference proceedings
Learning More Expressive General Policies for Classical Planning Domains
Proceedings of the AAAI Conference on Artificial Intelligence, 39 / edited by Toby Walsh, Julie Shah, Zico Kolter
39. Annual AAAI Conference on Artificial Intelligence, Meeting location,
Washington, DC, USA : AAAI Press, Proceedings of the AAAI Conference on Artificial Intelligence 39,25 (2025) [10.1609/aaai.v39i25.34872]
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Fulltext by arXiv.org