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, no5, , 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, no3, , 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, no3, , 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, no5, , 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, no1, , 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, no5, , 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, no1, , 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)