Reinforcement Learning | Markov Decision Process (MDP) | Which problems could be solved using RL

Well, let us accept the fact that not all problems could be solved using Reinforcement Learning.

But there are many problems that although prima-facie does not look like the right ones to apply RL, but could be very easily be converted into a Reinforcement Learning problem and a Reinforcement Learning agent could be trained to solve that problem.

This video explains in details:
- What is a Markov Decision Process or an MDP
- What is the relation of an MDP with respect to the Markov Process, Markov Chains, and the Decision Theory?
- Why Reinforcement Learning requires an MDP?
- How to know if a given problem fits into a Markov Decision Process?
- If a given problem does not fit into an MDP, can it be modified to satisfy the MDP assumptions?

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