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SUMMARY:World Models - Dr Gregor Simm (University of Cambridge)
DTSTART:20200318T110000Z
DTEND:20200318T123000Z
UID:TALK141271@talks.cam.ac.uk
CONTACT:75379
DESCRIPTION:A World Model is a generative recurrent neural network that is
  quickly trained in an unsupervised manner to model popular reinforcement 
 learning environments through compressed spatio-temporal representations. 
 Ha and Schmidhuber achieve state-of-the-art results for OpenAI Gym environ
 ments such as CarRacing-v0 by evolving a simple policy that uses these com
 pressed representations.\n\nIn our talk\, we will give an introduction to 
 Markov Decision Processes and Model-based reinforcement learning (RL). The
 n we dissect the Ha and Schmidhuber paper and describe more recent work ex
 panding on these ideas.\n
LOCATION:Hangouts Meet (Link provided via e-mail)
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