
Deep Reinforcement Learning
author: David Silver,
Department of Computer Science, University College London
published: July 28, 2015, recorded: June 2015, views: 13405
published: July 28, 2015, recorded: June 2015, views: 13405
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Description
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:
Great speed! The interruption every couple of seconds really give me the time to think about the material!
And just like in David's lectures, his laptop periodically shuts off because he forgot to plug it in. Brilliant.
Absolutely amazing talk, in any case.
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