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Reducing The Complexity Of Reinforcement Learning In POMDPs By Decomposition Into Decision And Perceptual Processes
(Computer Science & Engineering, 2013-03-20)
Markov Decision Processes (MDPs) and Partially Observable Markov Decision Processes (POMDPs) are very powerful and general frameworks to model decision and decision learning tasks in a wide range of problem domains. As a ...
Neural Image and Video Understanding
(2017-08-25)
Even though recent works on neural architectures have shown promising results at tasks like image recognition, object detection, playing Atari games, etc., learning a mapping from a visual space to a language space or vice ...