|COOKIES: By using this website you agree that we can place Google Analytics Cookies on your device for performance monitoring.|
Bayesian Reinforcement Learning
If you have a question about this talk, please contact Sinead Williamson.
Milica Gasic and Yunus Saatci will present on Bayesian Reinforcement learning.
Reading: A skim of Chapters 3 and 4 of Sutton and Barto and a skim of the following papers: A Bayesian Framework for Reinforcement Learning, An Analytic Solution to Discrete Bayesian Reinforcement Learning (Poupart et al., 2006), Reinforcement Learning with Gaussian Processes, Bayesian Policy Gradient
This talk is part of the Machine Learning Reading Group @ CUED series.
This talk is included in these lists:
Note that ex-directory lists are not shown.
Other listsClare Hall Thursday Lunchtime Talks EPRG Energy and Environment Seminar Series Lent 2009 Type the title of a new list here
Other talksDialect Death and the Structured Obsolescence Myth Does Photography Capture a Moment in Time? Physics of the Cytoskeleton & Morphogenesis (TBC) Late Opening & Conversation about Drawing “Leveraging social psychological theory to understand engagement with personalized genomic information in a genome sequencing trial” Purpose, Mastery, Corporate Agricultural Science – and why supporting Arsenal is good for your Career