Deep Reinforcement Learning

author: David Silver, Department of Computer Science, University College London
published: July 28, 2015,   recorded: June 2015,   views: 12161


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In this tutorial I will discuss how reinforcement learning (RL) can be combined with deep learning (DL). There are several ways to combine DL and RL together, including value-based, policy-based, and model-based approaches with planning. Several of these approaches have well-known divergence issues, and I will present simple methods for addressing these instabilities. The talk will include a case study of recent successes in the Atari 2600 domain, where a single agent can learn to play many different games directly from raw pixel input.

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Reviews and comments:

Comment1 Alan Flynn, May 24, 2016 at 4:10 p.m.:

Great speed! The interruption every couple of seconds really give me the time to think about the material!

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