Publikationen von P Dayan

Buchkapitel (13)

261.
Buchkapitel
Dayan, P.; Nakahara, H.: Models and Methods for Reinforcement Learning. In: Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience, Bd. 5: Methodology, 4. Aufl., S. 1 - 40 (Hg. Wixted, J.; Wagenmakers, E.-J.). Wiley, Hoboken, NJ, USA (2018)
262.
Buchkapitel
Dayan, P.: Exploration from Generalization Mediated by Multiple Controllers. In: Intrinsically Motivated Learning in Natural and Artificial Systems, S. 73 - 91 (Hg. Baldassarre, G.; Mirolli, M.). Springer, Berlin, Germany (2013)
263.
Buchkapitel
Dayan, P.: Models of Value and Choice. In: Neuroscience of Preference and Choice: Cognitive and Neural Mechanisms, 2, S. 33 - 52 (Hg. Dolan, R.; Sharot, T.). Elsevier/Academic Press, London, UK (2012)
264.
Buchkapitel
Daw, N.; Courville, A.; Dayan, P.: Semi-rational models of conditioning: The case of trial order. In: The Probabilistic Mind: Prospects for Bayesian cognitive science$, 19, S. 427 - 448 (Hg. Chater, N.; Oaksford, M.). Oxford University Press, Oxford, UK (2008)
265.
Buchkapitel
Platt, M.; Dayan, P.; Dehaene, S.; McCabe, H.; Menzel, R.; Phelps, E.; Plassmann, H.; Ratcliff, R.; Shadlen, M.; Singer, W.: Neuronal Correlates of Decision Making. In: Better than conscious?: decision making, the human mind, and implications for institutions, 6 (Hg. Engel, C.; Singer, W.). MIT Press, Cambridge, MA, USA (2008)
266.
Buchkapitel
Daw, N.; Niv, Y.; Dayan, P.: Actions, policies, values, and the basal ganglia. In: Recent Breakthroughs in Basal Ganglia Research, 8, S. 91 - 106 (Hg. Bezard, E.). Nova Science Publishers, Hauppauge, NY, USA (2006)
267.
Buchkapitel
Dayan, P.: Levels of Analysis in Neural Modeling. In: Encyclopedia of Cognitive Science, 2 Aufl. (Hg. Nadel, L.). Wiley, Chichester, UK (2005)
268.
Buchkapitel
Dayan, P.; Watkins, C.: Reinforcement Learning. In: Encyclopedia of Cognitive Science, Bd. 3 (Hg. Nadel, L.). Wiley, Chichester, UK (2005)
269.
Buchkapitel
Dayan, P.: Helmholtz machines and wake-sleep learning. In: The Handbook of Brain Theory and Neural Networks, 2. Aufl., S. 522 - 524 (Hg. Arbib, M.). MIT Press, Cambridge, MA, USA (2003)
270.
Buchkapitel
Schraudolph, N.; Dayan, P.; Sejnowski, T.: Learning to Evaluate Go Positions via Temporal Difference Methods. In: Computational Intelligence in Games, S. 77 - 98 (Hg. Baba, N.; Jain, L.). Physica Verlag, Heidelberg, Germany (2001)
271.
Buchkapitel
Dayan, P.: Unsupervised Learning. In: The MIT Encyclopedia of the Cognitive Sciences (Hg. Wilson, R.; Keil, F.). MIT Press, Cambridge, MA, USA (1999)
272.
Buchkapitel
Montague, P.; Dayan, P.: Neurobiological Modeling: Squeezing Top Down to Meet Bottom Up. In: A Companion to Cognitive Science, S. 526 - 542 (Hg. Bechtel, W.; Graham, G.). Blackwell, Malden, MA, USA (1998)
273.
Buchkapitel
Oberlander, J.; Dayan, P.: Altered states and virtual beliefs. In: Connectionism, Concepts and Folk Psychology: The Legacy of Alan Turing Vol. 2, S. 101 - 114 (Hg. Millican, P.; Clark, A.). Clarendon Press, Oxford, UK (1996)

Konferenzband (1)

274.
Konferenzband
Exploration and Curiosity in Robot Learning and Inference (Dagstuhl Reports, 1). Dagstuhl Seminar 11131, Dagstuhl, Germany, 27. März 2011 - 01. April 2011. (2011)

Konferenzbeitrag (80)

275.
Konferenzbeitrag
Tano, P.; Dayan, P.; Pouget, A.: A local temporal difference code for distributional reinforcement learning. In: Advances in Neural Information Processing Systems 33, S. 13662 - 13673 (Hg. Larochelle, H.; Ranzato, M.; Hadsell, R.; Balcan, M.-F.; Lin, H.-T.). 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 06. Dezember 2020 - 12. Dezember 2020. Curran, Red Hook, NY, USA (2021)
276.
Konferenzbeitrag
Ahilan, S.; Dayan, P.: Correcting Experience Replay for Multi-Agent Communication. In: Ninth International Conference on Learning Representations (ICLR 2021). Ninth International Conference on Learning Representations (ICLR 2021), Vienna, Austria, 03. Mai 2021 - 07. Mai 2021. (2021)
277.
Konferenzbeitrag
Sezener, E.; Dayan, P.: Static and Dynamic Values of Computation in MCTS. 36th Conference on Uncertainty in Artificial Intelligence (UAI 2020), 03. August 2020 - 06. August 2020. Proceedings of Machine Learning Research (PMLR) 124, 26, S. 31 - 40 (2020)
278.
Konferenzbeitrag
Browning, M.; Carter, C.; Chatham, C.; Den Ouden, H.; Gillan, C.; Baker, J.; Chekroud, A.; Cools, R.; Dayan, P.; Gold, J. et al.; Goldstein, R.; Hartley, C.; Kepecs, A.; Lawson, R.; Mourao-Miranda, J.; Phillips, M.; Pizzagalli, D.; Powers, A.; Rindskopf, D.; Roiser, J.; Schmack, K.; Schiller, D.; Sebold, M.; Stephan, K.; Frank, M.; Huys, Q.; Paulus, M.: Realizing the Clinical Potential of Computational Psychiatry: Report from the Banbury Center Meeting, February 2019. Banbury Center Meeting 2019, Huntington, NY, USA, 2019-02. Biological Psychiatry 88 (2), S. e5 - e10 (2020)
279.
Konferenzbeitrag
Dezfouli, A.; Ashtiani, H.; Ghattas, O.; Nock, R.; Dayan, P.; Ong, C.: Disentangled behavioural representations. In: Advances in Neural Information Processing Systems 32, S. 2243 - 2252 (Hg. Wallach, H.; Larochelle, H.; Beygelzimer , A.; d'Alché-Buc, F.; Fox, E. et al.). Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada, 09. Dezember 2019 - 13. Dezember 2019. Curran, Red Hook, NY, USA (2020)
280.
Konferenzbeitrag
Jain, Y.; Gupta, S.; Rakesh, V.; Dayan, P.; Callaway, F.; Lieder, F.: How do people learn how to plan? In: Conference on Cognitive Computational Neuroscience (CCN 2019), PS-2A.70, S. 826 - 829. Conference on Cognitive Computational Neuroscience (CCN 2019), Berlin, Germany, 13. September 2019 - 16. September 2019. (2019)
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