Expected Return - What Drives a Reinforcement Learning Agent in an MDP

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Welcome back to this series on reinforcement learning! In this video, we're going to build on the way we think about the cumulative rewards that an agent receives in a Markov decision process and introduce the important concept of return.

We'll see that the return is exactly what's driving the agent to make the decisions it makes. We'll also introduce the idea of episodes and talk about episodic tasks vs. continuing tasks.

Sources:
Reinforcement Learning: An Introduction, Second Edition by Richard S. Sutton and Andrew G. Bartow
http://incompleteideas.net/book/RLboo...

Playing Atari with Deep Reinforcement Learning by Deep Mind Technologies
https://www.cs.toronto.edu/~vmnih/doc...

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