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An introduction to Reinforcement Learning

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Reinforcement learning is inspired by the way people and most animals learn to interact with an environment. Animals are motivated by reward: they try actions and then try to remember the corresponding reward. Later, if they are in a similar situation, they can remember what action needed to be taken to achieve a reward. During my talk I will explore the basics of reinforcement learning, go into more depth of the DQN algorithm applied on Atari games and explore ways the algorithm can be improved. I will also introduce the AC3 (Asynchronous Advantage Actor-Critic) algorithm and explore successes and current research opportunities in the area.

This talk is part of the Churchill CompSci Talks series.

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