Welcome to this series on reinforcement learning! In this video, we will discuss Markovian decision processes, or MDPs. Markovian decision processes allow us to formalize sequential decision-making. This formalization is the basis of structuring problems which are solved by reinforcement learning.

We will detail the components that make up a MDP, including: the environment, the agent, the states of the environment, the actions that the agent can take in the environment and the rewards that can be given to the agent for his actions.

Sources:
Reinforcement Learning: An Introduction, Second Edition by Richard S. Sutton and Andrew G. Bartow
http://incompleteideas.net/book/RLbook2020.pdf

Playing Atari with Deep Reinforcement Learning by Deep Mind Technologies
https://www.cs.toronto.edu/vmnih/docs/dqn.pdf

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