Deep Learning: Reinforcement Learning - Part 5
Channel: Andreas Maier
Date: 17/06/2020

Deep Learning: Reinforcement Learning - Part 5

In the last video on reinforcement learning, we look into the deep reinforcement learning techniques. We start looking into how Deep Mind beat Atari Games and in particular breakout. Furthermore, we look into the technology behind AlphaGo and AlphaGoZero to play Go, Chess, and Shogi on world-class level.

Full Transcript
https://towardsdatascience.com/reinforcement-learning-part-5-70d10e0ca3d9

Links
Link to Sutton's Reinforcement Learning in its 2018 draft, including Deep Q learning and Alpha Go details
http://incompleteideas.net/book/bookdraft2018jan1.pdf

Video References:
Breakout Example 1
https://youtu.be/eG1Ed8PTJ18

Breakout Example 2
https://youtu.be/V1eYniJ0Rnk

AlphaGo Lee Sedol Match 3
https://youtu.be/qssMuKtorkk

AlphaGo Lee Sedol Match 4
https://youtu.be/-D3MyAm3JFo

Music
Beethoven - Moonlight Sonata
https://www.youtube.com/watch?v=pVAqHvxz7ao



Further Reading:
A gentle Introduction to Deep Learning
https://www.sciencedirect.com/science/article/pii/S093938891830120X

Silent Partner - Fire Breather
https://youtu.be/hFQ7fj5-Zqg

References
[1] David Silver, Aja Huang, Chris J Maddison, et al. “Mastering the game of Go with deep neural networks and tree search”. In: Nature 529.7587 (2016), pp. 484–489.
[2] David Silver, Julian Schrittwieser, Karen Simonyan, et al. “Mastering the game of go without human knowledge”. In: Nature 550.7676 (2017), p. 354.
[3] David Silver, Thomas Hubert, Julian Schrittwieser, et al. “Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm”. In: arXiv preprint arXiv:1712.01815 (2017).
[4] Volodymyr Mnih, Koray Kavukcuoglu, David Silver, et al. “Human-level control through deep reinforcement learning”. In: Nature 518.7540 (2015), pp. 529–533.
[5] Martin Müller. “Computer Go”. In: Artificial Intelligence 134.1 (2002), pp. 145–179.
[6] Richard S. Sutton and Andrew G. Barto. Introduction to Reinforcement Learning. 1st. Cambridge, MA, USA: MIT Press, 1998.