Covers: theory of Markov Decision Processes (MDPs)

- What are Bellman equations?
- What is Value iteration?
- What is Policy iteration?

This video covers the detailed explanation of concepts around MDP like Bellman Equation, Policy Iteration and Value Iteration. It's highly recommended to watch the full lecture video.

Fail to play? Open the link directly: https://www.youtube.com/watch?v=6pBvbLyn6fE&list=PLNozK-HB4MXsVAN6cqkCAO09RChbIAk5i&index=10

Pieter Abbeel

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Contributors

- Objectives
- Basic understanding of model-free approaches for policy evaluation
- Potential Use Cases
- Strategic Games, Robotics
- Who is This For ?
- BEGINNERAnyone who is interested in learning the concepts and real world applications of Reinforcement Learning

Click on each of the following **annotated items** to see details.

Resources6/6

ARTICLE 1. What are expected values, variance, and covariance?

- What are expected values and how do these relate to the concept of covariance?

20 minutes

OTHER 2. Monte-Carlo (MC) Policy Evaluation

- What is Monte-Carlo policy evaluation technique?

20 minutes

OTHER 3. Temporal Difference (TD) Policy Evaluation

- What is Temporal Difference (TD) policy evaluation?

15 minutes

BOOK_CHAPTER 4. MDP, MC and TD sections from Reinforcement Learning book

- What is Markov Decision Process (MDP)?
- What is Monte-Carlo (MC) Learning?
- What is Temporal Difference (TD) Learning?

30 minutes

VIDEO 5. Markov Decision Processes - Part 1

- Definition of Markov Decision Processes?
- What is Markov about MDPs?
- What is V-value and Q-value?

30 minutes

VIDEO 6. Markov Decision Processes - Part 2

- What are Bellman equations?
- What is Value iteration?
- What is Policy iteration?

30 minutes

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