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Learning Lifted STRIPS Models from Action Traces Alone: A Simple, General, and Scalable Solution
; ;
2024 & 2025
Submitted on 22 Nov 2024 (v1), last revised 2 May 2025 (this version, v2)
Online
DOI: 10.48550/arXiv.2411.14995
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:2411.14995
OpenAlex: W4404987618
Interne Identnummern
RWTH-2025-02462
Datensatz-ID: 1006387
Related:
Contribution to a book/Contribution to a conference proceedings
Learning Lifted STRIPS Models from Action Traces alone: A Simple, General, and Scalable Solution
Proceedings of the Thirty-Fifth International Conference on Automated Planning and Scheduling / Edited by Daniel Harabor, Miquel Ramirez
35. International Conference on Automated Planning and Scheduling, ICAPS 2025, MelbourneMelbourne, Australia, 9 Nov 2025 - 14 Nov 2025
Washington, DC, USA : AAAI Press, Proceedings of the International Conference on Automated Planning and Scheduling 35, 1 189-197 (2025) [10.1609/icaps.v35i1.36117]
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Fulltext by arXiv.org