The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
If multi-agent learning is the answer, what is the question?
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Citations
Cites
Reinforcement Learning: An Introduction
Sutton, R. S., & Barto, A. G. (1998) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.1998.712192 · Cited by 27,225
A decision-theoretic generalization of on-line learning and an application to boosting
Freund, Y., & Schapire, R. E. (1997) · Journal of Computer and System Sciences · doi:10.1006/jcss.1997.1504 · Cited by 20,466
Bellman, R. E. (2010) · doi:10.1515/9781400835386 · Cited by 14,588
Watkins, C. J. C. H., & Dayan, P. (1992) · Machine Learning · doi:10.1007/bf00992698 · Cited by 9,083
Reinforcement Learning: A Survey
Kaelbling, L. P., Littman, M. L., & Moore, A. W. (1996) · Journal of Artificial Intelligence Research · doi:10.1613/jair.301 · Cited by 8,972
An Iterative Method of Solving a Game
Robinson, J. (1951) · The Annals of Mathematics · doi:10.2307/1969530 · Cited by 868
Cited by
Multiagent systems: algorithmic, game-theoretic, and logical foundations
(2009) · Choice Reviews Online · doi:10.5860/choice.46-5662 · Cited by 1,756
Nguyen, T. T., Nguyen, N. D., & Nahavandi, S. (2020) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2020.2977374 · Cited by 1,306
Deep Reinforcement Learning: An Overview
Li, Y. (2017) · arXiv · doi:10.48550/arxiv.1701.07274 · Cited by 762
Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving
Shalev-Shwartz, S., Shammah, S., & Shashua, A. (2016) · arXiv · doi:10.48550/arxiv.1610.03295 · Cited by 509
Silver, D., Singh, S., Precup, D., & Sutton, R. S. (2021) · Artificial Intelligence · doi:10.1016/j.artint.2021.103535 · Cited by 445
Metadata
- Authors
- Shoham, Y., Powers, R., & Grenager, T.
- Venue
- Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 2007-05
- Volume
- 171
- Issue
- 7
- Pages
- 365-377
- ISSN
- 0004-3702 (ISSN-L)
- OpenAlex
- W2156194062
- Cited by
- 410
- References
- 6
- FWCI
- 49.25
- Type
- journal article
- Language
- en
- Open access
- bronze
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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.
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Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: If multi-agent learning is the answer, what is the question? https://app.cochat.ai/papers/10.1016/j.artint.2006.02.006
- The paper
- Shoham, Y., Powers, R., & Grenager, T. (2007). If multi-agent learning is the answer, what is the question? Artificial Intelligence. https://doi.org/10.1016/j.artint.2006.02.006
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.
