Publikationen von P Dayan

Dayan, P.; Sejnowski, T.: The Variance of Covariance Rules for Associative Matrix Memories and Reinforcement Learning. Neural computation 5 (2), S. 205 - 209 (1993)

Dayan, P.: The Convergence of TD(λ) for General λ. Machine Learning 8 (3-4), S. 341 - 362 (1992)

Watkins, C.; Dayan, P.: Q-learning. Machine Learning 8 (3-4), S. 279 - 292 (1992)

Dayan, P.; Willshaw, D.: Optimising synaptic learning rules in linear associative memories. Biological Cybernetics 65 (4), S. 253 - 265 (1991)

Willshaw, D.; Dayan, P.: Optimal Plasticity from Matrix Memories: What Goes Up Must Come Down. Neural computation 2 (1), S. 85 - 93 (1990)

Willshaw, D.; Dayan, P.: Optimal plasticity in matrix memories: What goes up must come down. Neural computation 2 (1), S. 85 - 93 (1990)

Robertson, M.; Ritchie, S.; Dayan, P.: Semiconductor waveguides: analysis of optical propagation in single rib structures and directional couplers. Proceedings of the Institution of Electrical Engineers Part J: Optoelectronics 132 (6), S. 336 - 342 (1985)

Dayan, P.; Abbott, L.: Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. MIT Press, Cambridge, MA, USA (2001), 460 S.

Brielmann, A.; Dayan, P.: Aesthetic boredom. In: The Routledge International Handbook of Boredom (Hg. Bieleke, M.; Wolff, W.; Martarelli, C.). Routledge, London, UK (2024)

Dayan, P.; Roiser, J.; Viding, E.: The first steps on long marches: The costs of active observation. In: Psychiatry Reborn: Biopsychosocial psychiatry in modern medicine, 14, S. 213 - 228 (Hg. Davies, W.; Savulescu, J.; Roache, R.; Loebel, J.). Oxford University Press, Oxford, UK (2020)

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. 507 - 546 (Hg. Wixted, J.; Wagenmakers, E.-J.). Wiley, Hoboken, NJ, USA (2018)

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)

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)

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)

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)

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)

Dayan, P.: Levels of Analysis in Neural Modeling. In: Encyclopedia of Cognitive Science, 2 Aufl. (Hg. Nadel, L.). Wiley, Chichester, UK (2005)

Dayan, P.; Watkins, C.: Reinforcement Learning. In: Encyclopedia of Cognitive Science, Bd. 3 (Hg. Nadel, L.). Wiley, Chichester, UK (2005)

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)

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)