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DTSTART:20050403T070000
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DTSTART;TZID=America/Toronto:20060217T113000
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URL:https://uwaterloo.ca/artificial-intelligence-group/events/ai-seminar-an
 alytic-solution-discrete-bayesian-reinforcement
LOCATION:DC - William G. Davis Computer Research Centre 200 University Aven
 ue West 2306C (AI lab) Waterloo ON N2L 3G1 Canada
SUMMARY:AI seminar: An analytic solution to discrete Bayesian reinforcement
 \nlearning
CLASS:PUBLIC
DESCRIPTION:Speaker: Pascal Poupart\n\nReinforcement learning (RL) was orig
 inally proposed as a framework to\nallow agents to learn in an online fash
 ion as they interact with their\nenvironment. Existing RL algorithms come 
 short of achieving this goal\nbecause the amount of exploration required i
 s often too costly and/or\ntoo time consuming for online learning. As a re
 sult\, RL is mostly used\nfor offline learning in simulated environments. 
 We propose a new\nalgorithm\, called BEETLE\, for effective online learnin
 g that is\ncomputationally efficient while minimizing the amount of explor
 ation.
DTSTAMP:20260318T034139Z
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