Publikationen von P Dayan

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)

Dayan, P.: Unsupervised Learning. In: The MIT Encyclopedia of the Cognitive Sciences (Hg. Wilson, R.; Keil, F.). MIT Press, Cambridge, MA, USA (1999)

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)

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)

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

Bucher, S.; Dayan, P.: Algorithmic Choice Architecture for Boundedly Rational Consumers. In: Advances in Neural Information Processing Systems 36: 37th Conference on Neural Information Processing Systems (NeurIPS 2023). NeurIPS Workshop on Information-Theoretic Principles in Cognitive Systems (InfoCog @ NeurIPS 2023), New Orleans, LA, USA, 15. Dezember 2023. (2023)

Saanum, T.; Éltetö, N.; Dayan, P.; Binz, M.; Schulz, E.: Reinforcement Learning with Simple Sequence Priors. In: Advances in Neural Information Processing Systems 36: 37th Conference on Neural Information Processing Systems (NeurIPS 2023). Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, LA, USA, 10. Dezember 2023 - 16. Dezember 2023. (2023)

Bruijns, S.; Dayan, P.; The International Brain Laborartory: Understanding Learning Trajectories With Infinite Hidden Markov Models. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.97, S. 770 - 772. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Ershadmanesh, S.; Gholamzadeh, A.; Desender, K.; Dayan, P.: Meta-cognitive Efficiency in Learned Value-based Choice. In: 2023 Conference on Cognitive Computational Neuroscience, P-1A.9, S. 29 - 32. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Renz, F.; Grossman, S.; Schuck, N.; Dayan, P.; Doeller, C.: Learning and adapting cognitive maps for flexible decision-making. In: 2023 Conference on Cognitive Computational Neuroscience, P-3.35, S. 999 - 1001. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Rubino, V.; Dayan, P.; Wu, C.: Biases towards compositionally simpler hypotheses are robust and unaffected by learning. In: 2023 Conference on Cognitive Computational Neuroscience, P-2B.50, S. 817 - 820. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Safavi, S.; Dayan, P.: A decision-theoretic model of perceptual multistability: perceptual switches as internal actions. In: 2023 Conference on Cognitive Computational Neuroscience, P-3.41, S. 1022 - 1024. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Shen, T.; Dayan, P.: Risking your Tail: Curiosity, Danger & Exploration. In: 2023 Conference on Cognitive Computational Neuroscience, P-3.67, S. 1113 - 1116. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Shen, T.; Dayan, P.; Bányai, M.: Meta-cognitive planning for learning representations. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.1, S. 425 - 428. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)