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Introduction to Reinforcement Learning

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Description

Reinforcement learning is a branch of machine learning, in which in algorithm learns a good policy for acting in an environment of interest, based on experience. When interacting with the environment, an agent (algorithm) experiences rewards or costs, based upon actions taken in particular situations. The algorithm learns a policy by “reinforcing” (learning to favor) actions that yield high rewards. In this introduction to reinforcement learning, basic concepts like Q-learning will be developed. In addition, we will discuss how deep learning (neural networks) have impacted reinforcement learning, including a discussion of how the Alpha-Go system developed by Google Deep Mind was able to defeat the best human players in the game Go.


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Details

Status Archived
Date Thursday, February 21st, 2019
Time 4:00pm - 6:00pm
Location The Edge Workshop
Leader Lawrence Carin
Enrolled 50 of 50

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