Peter Samuel Dayan FRS was until Sep. 30th, 2018 a professor of the Gatsby Charitable Foundation Computational Neuroscience Unit at University College London.. Currently, he is a director at the Max Planck Institute for Biological Cybernetics. He is co-author of Theoretical Neuroscience, a textbook on Computational neuroscience. He is known for applying Bayesian methods from machine learning and artificial intelligence to understand neural function, and is particularly recognized for having related neurotransmitter levels to prediction errors and Bayesian uncertainties. He co-authored a paper on Q-learning with Chris Watkins,[clarification needed] and provided a proof of convergence of TD(λ) for arbitrary λ.
Peter Samuel Dayan|
1965 (age 52–53)
University of Cambridge (BA)|
University of Edinburgh (PhD)
Rumelhart Prize (2012)|
The Brain Prize (2017)
Max Planck Institute for Biological Cybernetics, Tübingen|
University College London
Massachusetts Institute of Technology
University of Toronto
|Thesis||Reinforcing connectionism : learning the statistical way (1991)|
|Doctoral advisor||David Willshaw|
Dayan studied mathematics at the University of Cambridge and then continued for a PhD in artificial intelligence at the University of Edinburgh on statistical learning  with David Willshaw and David Wallace, focusing on associative memory and reinforcement learning.
Career and researchEdit
After his PhD, Dayan held postdoctoral research positions with Terry Sejnowski at the Salk Institute and Geoffrey Hinton at the University of Toronto. He then took up an assistant professor position at the Massachusetts Institute of Technology, and moved to the Gatsby Computational Neuroscience Unit at University College London in 1998, becoming professor and director in 2002. He stepped down as director in 2017. In September 2018, the Max Planck Society announced his appointment as a director at the Max Planck Institute for Biological Cybernetics.
Awards and honoursEdit
- Ghahramani, Zoubin (2017). "Welcoming Peter Dayan to Uber AI Labs". uber.com.
- "Peter Dayan". www.gatsby.ucl.ac.uk.
- Schultz, W., Dayan, P., & Montague, P. R. (1997). A neural substrate of prediction and reward. Science, 275 (5306), 1593–1599 doi:10.1126/science.275.5306.1593
- Watkins, Christopher JCH, and Peter Dayan. "Q-learning". Machine learning 8, no. 3–4 (1992): 279–292. doi:10.1007/BF00992698
- Dayan, Peter. "The convergence of TD (λ) for general λ". Machine learning 8, no. 3–4 (1992): 341–362 doi:10.1023/A:1022632907294
- Dayan, Peter Samuel (1991). Reinforcing connectionism: learning the statistical way. lib.ed.ac.uk (PhD thesis). hdl:1842/14754. EThOS uk.bl.ethos.649240.
- "Peter Dayan and Li Zhaoping appointed to the Max Planck Institute for Biological Cybernetics". mpg.de. Retrieved 2 October 2018.
- Anon (2018). "Professor Peter Dayan FRS". royalsociety.org. London: Royal Society. Retrieved 22 May 2018. One or more of the preceding sentences incorporates text from the royalsociety.org website where:
“All text published under the heading 'Biography' on Fellow profile pages is available under Creative Commons Attribution 4.0 International License.” --Royal Society Terms, conditions and policies at the Wayback Machine (archived 2016-11-11)
|This biography of an academic is a stub. You can help Wikipedia by expanding it.|
|This article about a neuroscientist is a stub. You can help Wikipedia by expanding it.|