The DOI matches its Crossref record.
SHOP2: An HTN Planning System
Open accessAbstract
The SHOP2 planning system received one of the awards for distinguished performance in the 2002 International Planning Competition. This paper describes the features of SHOP2 which enabled it to excel in the competition, especially those aspects of SHOP2 that deal with temporal and metric planning domains.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Automated machine learning: Review of the state-of-the-art and opportunities for healthcare
Waring, J., Lindvall, C., & Umeton, R. (2020) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2020.101822 · Cited by 834
Hierarchically organized behavior and its neural foundations: A reinforcement learning perspective
Botvinick, M. M., Niv, Y., & Barto, A. G. (2009) · Cognition · doi:10.1016/j.cognition.2008.08.011 · Cited by 646
Web services composition: A decade’s overview
Sheng, Q. Z., Qiao, X., Vasilakos, A. V., Szabo, C., Bourne, S., & Xu, X. (2014) · Information Sciences · doi:10.1016/j.ins.2014.04.054 · Cited by 389
Learning action models from plan examples using weighted MAX-SAT
Yang, Q., Wu, K., & Jiang, Y. (2007) · Artificial Intelligence · doi:10.1016/j.artint.2006.11.005 · Cited by 206
Logic-based technologies for multi-agent systems: a systematic literature review
Calegari, R., Ciatto, G., Mascardi, V., & Omicini, A. (2021) · Autonomous Agents and Multi-Agent Systems · doi:10.1007/s10458-020-09478-3 · Cited by 117
“[267] and JSHOP2 by Ilghami [197]—are domain-independent automatedplanning systems based on ordered task decomposition, which is a type of Hierarchical Task Network (HTN) planning—see Erol et al.”
Method
Metadata
- Authors
- Nau, D. S., Au, T. C., Ilghami, O., Kuter, U., Murdock, J. W., Wu, D., & Yaman, F.
- Venue
- Journal of Artificial Intelligence Research
- Publisher
- AI Access Foundation
- Published
- 2003-12-01
- Volume
- 20
- Pages
- 379-404
- ISSN
- 1076-9757 (ISSN-L)
- OpenAlex
- W2147357263
- Cited by
- 947
- References
- 0
- FWCI
- 34.98
- Type
- journal article
- Language
- en
- Open access
- diamond
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: SHOP2: An HTN Planning System. https://app.cochat.ai/papers/10.1613/jair.1141
- The paper
- Nau, D. S., Au, T. C., Ilghami, O., Kuter, U., Murdock, J. W., Wu, D., & Yaman, F. (2003). SHOP2: An HTN Planning System. Journal of Artificial Intelligence Research. https://doi.org/10.1613/jair.1141
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
