Basics of Computational Reinforcement Learning

author: Michael Littman, Department of Computer Science, Rutgers, The State University of New Jersey
published: July 28, 2015,   recorded: June 2015,   views: 1118
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Description

In machine learning, the problem of reinforcement learning is concerned with using experience gained through interacting with the world and evaluative feedback to improve a system’s ability to make behavioral decisions. This tutorial will introduce the fundamental concepts and vocabulary that underlie this field of study. It will also review recent advances in the theory and practice of reinforcement learning, including developments in fundamental technical areas such as generalization, planning, exploration and empirical methodology.

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Comment1 HW, December 1, 2016 at 10:29 a.m.:

The videos seem to break too frequently. It is almost impossible to stay focused (I have checked my internet speed, etc.: it is fine). I had the same experience with Silver's "Deep Reinforcement Learning" tutorial video (http://videolectures.net/rldm2015_sil...

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