Event Abstract

Model-based and model-free reinforcement learning: the experiments

  • 1 University College London, Gatsby Computational Neuroscience Unit, United Kingdom

A recent direction in neural reinforcement learning is to consider multiple mechanisms involved in control. Two of the three that have been identified are model-based and model-free instrumental systems, and their individual characteristics and interactions are now the focus of various theoretically-directed experiments. I will discuss some of our recent attempts, which offer both support and complication for the original suggestions. I will also describe a further experiment that reminds us that we ignore Pavlovian influences at our peril.

Parts are joint work with: Ray Dolan, Nathaniel Daw, Neir Eshel, Jan Glascher, Quentin Huys, John O'Doherty, Jon Roiser, Klaus Wunderlich

Keywords: Model-based and model-free reinforcement learning:

Conference: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011, Freiburg, Germany, 4 Oct - 6 Oct, 2011.

Presentation Type: Keynote

Topic: other

Citation: Dayan P (2011). Model-based and model-free reinforcement learning: the experiments. Front. Comput. Neurosci. Conference Abstract: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011. doi: 10.3389/conf.fncom.2011.53.00019

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Received: 26 Sep 2011; Published Online: 04 Oct 2011.

* Correspondence: Prof. Peter Dayan, University College London, Gatsby Computational Neuroscience Unit, London, United Kingdom, dayan@gatsby.ucl.ac.uk