The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Reinforcement learning with replacing eligibility traces
Open accessOverview
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
Cites
Bellman, R. E. (2010) · doi:10.1515/9781400835386 · Cited by 14,588
Learning to predict by the methods of temporal differences
Sutton, R. S. (1988) · Machine Learning · doi:10.1007/bf00115009 · Cited by 5,148
Self-citationSimulation and the Monte Carlo Method
Rubinstein, R. Y., & Kroese, D. P. (2016) · Wiley Series in Probability and Statistics · doi:10.1002/9781118631980 · Cited by 3,356 · cited 2×
“This suggests that one might estimate a state's value simply by averaging all the returns that follow it. This is what is classically done in Monte Carlo (MC) prediction methods ( Rubinstein, 1981; Curtiss, 1954; Wasow, 1952; Barto & Duff, 1994).”
BackgroundMethodSelf-improving reactive agents based on reinforcement learning, planning and teaching
Lin, L.-J. (1992) · Machine Learning · doi:10.1007/bf00992699 · Cited by 1,564
Cited by
Mastering the game of Go without human knowledge
Silver, D., Schrittwieser, J., Simonyan, K., Antonoglou, I., Huang, A., Guez, A., Hubert, T., Baker, L., Lai, M., Bolton, A., et al. (2017) · Nature · doi:10.1038/nature24270 · Cited by 9,084
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
AntNet: Distributed Stigmergetic Control for Communications Networks
Di Caro, G., & Dorigo, M. (1998) · Journal of Artificial Intelligence Research · doi:10.1613/jair.530 · Cited by 1,579
Medial prefrontal cortex as an action-outcome predictor
Alexander, W. H., & Brown, J. W. (2011) · Nature Neuroscience · doi:10.1038/nn.2921 · Cited by 1,000
Algorithms for Reinforcement Learning
Szepesvári, C. (2010) · Synthesis Lectures on Artificial Intelligence and Machine Learning · doi:10.1007/978-3-031-01551-9 · Cited by 1,049
Metadata
- Authors
- Singh, S. P., & Sutton, R. S.
- Venue
- Machine Learning
- Published
- 1996
- Volume
- 22
- Issue
- 1-3
- Pages
- 123-158
- ISSN
- 0885-6125 (ISSN-L)
- 1573-0565
- OpenAlex
- W2113913482
- Cited by
- 575
- References
- 4
- FWCI
- 15.86
- Type
- journal article
- Language
- en
- Open access
- bronze
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
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.
