AlphaGo - Mastering the game of Go with deep neural networks and tree search | RL Paper Explained

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In this video, I cover the seminal AlphaGo paper - the first system to beat a professional Go player in the game of Go.

A task previously considered beyond the reach of current AI systems and at least 10 years off into the future, but neural networks proved them wrong!

You'll learn about:
✔️All of the nitty-gritty details around AlphaGo
✔️How MTCS and other subcomponents work

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✅ AlphaGo movie: https://www.youtube.com/watch?v=WXuK6gekU1Y&ab_channel=DeepMind
✅ Karpathy on AlphaGo: https://medium.com/@karpathy/alphago-in-context-c47718cb95a5
✅ Silver on UCB algo: https://www.youtube.com/watch?v=sGuiWX07sKw&list=PLqYmG7hTraZBiG_XpjnPrSNw-1XQaM_gB&index=12&t=2370s&ab_channel=DeepMind
✅ MTCS explained: https://www.youtube.com/watch?v=UXW2yZndl7U
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⌚️ Timetable:

00:00 Intro
00:37 Context behind the game of Go
04:10 High-level overview of components - SL policies
07:25 RL policy network
09:30 The value network
11:15 Going deeper
16:30 Details around value network
19:05 Understanding the search (MTCS)
27:10 Evaluation of AlphaGo
33:30 Older techniques
34:40 Even more detailed explanation of APV-MTCS
37:40 Virtual loss
41:00 Engineering
45:30 Neural networks and symmetries

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#alphago #deepmind #reinforcementlearning

Видео AlphaGo - Mastering the game of Go with deep neural networks and tree search | RL Paper Explained канала Aleksa Gordić - The AI Epiphany