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UID:567@lincs.fr
DTSTART;TZID=Europe/Paris:20201007T110000
DTEND;TZID=Europe/Paris:20201007T120000
DTSTAMP:20201012T064355Z
URL:https://www.lincs.fr/events/zap-stochastic-approximation-and-reinforce
 ment-learning/
SUMMARY:Zap Stochastic Approximation and Reinforcement Learning
DESCRIPTION:Many reinforcement learning problems can be seen from the point
 of view of stochastic approximation. Unfortunately\, classic stochastic
 approximation algorithms\, such as Robbins-Monro\, may have an infinite
 asymptotic variance. The class of "zap" algorithms aim at solving that
 problem. We then examine the application of zap algorithms to reinforcement
 learning\, with the example of zap Q-learning.\n\nSlides
CATEGORIES:Network Theory,Working Group,Youtube
LOCATION:Paris-Rennes Room (EIT Digital)\, 23 avenue d'Italie\, 75013
 Paris\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=23 avenue d'Italie\, 75013
 Paris\, France;X-APPLE-RADIUS=100;X-TITLE=Paris-Rennes Room (EIT
 Digital):geo:0,0
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TZID:Europe/Paris
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DTSTART:20200329T030000
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