Peter Dayan is the director of the Gatsby Computational Neuroscience Unit at University College London.He is co-author of "Theoretical Neuroscience", a leading textbook in computational and mathematical modeling of brain function (see Computational Neuroscience). He is known for applying Bayesian methods from Machine Learning and Artificial Intelligence to understand neural function, and is particularly renowned for having related neurotransmitter levels to prediction errors and Bayesian uncertainties.He co-authored "Q-learning" with Chris Watkins, and provided a proof of convergence of TD(?) for arbitrary ? (see temporal difference learning).His h-index according to Google Scholar is 65.He was awarded the 2013 Rumelhart Prize for Contributions to the Theoretical Foundations of Human Cognition.