Markov Decision Processes (MDPs) - Structuring a Reinforcement Learning Problem

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Welcome back to this series on reinforcement learning! In this video, we'll discuss Markov decision processes, or MDPs. Markov decision processes give us a way to formalize sequential decision making. This formalization is the basis for structuring problems that are solved with reinforcement learning.

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

Sources:
Reinforcement Learning: An Introduction, Second Edition by Richard S. Sutton and Andrew G. Bartow

Playing Atari with Deep Reinforcement Learning by Deep Mind Technologies

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Check out the corresponding blog and other resources for this video at:

deeplizard
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Can we take a second and just appreciate the work put in producing such high-quality videos in bites that are easy to understand?

beltusnkwawir
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Thanks deeplizard for doing the hard work on illustrations to explain it to the feeble-minded. Its like training a donkey, how to solve calculus.

aparvkishnov
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this is by far the best tutorial I've seen about this topic. I'm about to watch the whole series :D

SandwichMitGurke
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I’m so glad you produced this series of videos. I was intimidated by all the math and algorithm variations covered in the first four lectures of my graduate course. After watching these videos and then revisiting my grad lectures, I now actually understand what my professor was trying to teach. Thank you!

mike
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I saw different channels but no one explained this topic better than you . thanks alot

amirhosseinesteghamat
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I was wandering here and there looks like I have landed a perfect place to learn Deep Learning.... Thanks .. I will continue.

alokk
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You are awesome.
This series would help me for my project.
Thank you so much.
Best regards...

muomgu
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This series is awesome. Make learning a lot easier. Thank you so much.

ziaurrehman
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- **Introduction to Markov Decision Processes (MDPs)**:
- 0:00 - 0:17

- **Components of MDPs**:
- 0:23 - 1:43

- **Mathematical Representation of MDPs**:
- 1:47 - 3:59

- **Probability Distributions and Transition Probabilities**:
- 4:02 - 4:56

- **Conclusion and Next Steps**:
- 5:01 - 5:47

theliterunner
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Keep up the good work, thank you for the time your are putting on making this series :)

sahand
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amazing explanation of what is RL. I will watch the whole series from now

danielzoulla
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Seriously... Amazing tutorial! I really like how you offer text version as well. Thanks you :)

haneulkim
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Very intuitive and easy explanation. Thank you! 🤗😀

ilovemusic
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Great tutorial, understood the concept clearly for the first time, after going through many. Thank you very much.

thusharadunumalage
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Great video with intuitive explanations 👌

Galinator
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Thank you so much it is very clear the explanation of MDPs.

christopherherrera
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Second video completed, the video was clear as day

asdfasdfuhf
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This video can be denoted by n as n approaches perfection.

nossonweissman
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very very very very help full..thnks for making these videos..pls keep it going

harshadevapriyankarabandar