T.J. Sejnowski, P. Dayan et P.R. Montague, « Predictive hebbian learning », Proceedings of Eighth ACM Conference on Computational Learning Theory, , p. 15–18 (DOI10.1145/230000/225300/p15-sejnowski, lire en ligne)
P. R. Montague, P. Dayan et T. J. Sejnowski, « A framework for mesencephalic dopamine systems based on predictive Hebbian learning », The Journal of Neuroscience, vol. 16, no 5, , p. 1936–1947 (ISSN0270-6474, PMID8774460, DOI10.1523/JNEUROSCI.16-05-01936.1996)
T.J. Sejnowski, P. Dayan et P.R. Montague, « Predictive hebbian learning », Proceedings of Eighth ACM Conference on Computational Learning Theory, , p. 15–18 (DOI10.1145/230000/225300/p15-sejnowski, lire en ligne)
Gerald Tesauro, « Temporal Difference Learning and TD-Gammon », Communications of the ACM, vol. 38, no 3, , p. 58–68 (DOI10.1145/203330.203343, lire en ligne, consulté le )
Gerald Tesauro, « Temporal Difference Learning and TD-Gammon », Communications of the ACM, vol. 38, no 3, , p. 58–68 (DOI10.1145/203330.203343, lire en ligne, consulté le )
P. R. Montague, P. Dayan et T. J. Sejnowski, « A framework for mesencephalic dopamine systems based on predictive Hebbian learning », The Journal of Neuroscience, vol. 16, no 5, , p. 1936–1947 (ISSN0270-6474, PMID8774460, DOI10.1523/JNEUROSCI.16-05-01936.1996)
P. R. Montague et T. J. Sejnowski, « The predictive brain: temporal coincidence and temporal order in synaptic learning mechanisms », Learning & Memory, vol. 1, no 1, , p. 1–33 (ISSN1072-0502, PMID10467583)
P. R. Montague, P. Dayan et T. J. Sejnowski, « A framework for mesencephalic dopamine systems based on predictive Hebbian learning », The Journal of Neuroscience, vol. 16, no 5, , p. 1936–1947 (ISSN0270-6474, PMID8774460, DOI10.1523/JNEUROSCI.16-05-01936.1996)
P. R. Montague et T. J. Sejnowski, « The predictive brain: temporal coincidence and temporal order in synaptic learning mechanisms », Learning & Memory, vol. 1, no 1, , p. 1–33 (ISSN1072-0502, PMID10467583)
P.R. Montague, P. Dayan, S.J. Nowlan, A. Pouget et T.J. Sejnowski, « Using aperiodic reinforcement for directed self-organization », Advances in Neural Information Processing Systems, vol. 5, , p. 969–976 (lire en ligne)