RL Course by David Silver - Lecture 1: Introduction to Reinforcement Learning

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Strong rec colmvp · 2020-04 · on “ACM Prize in Computing Awarded to AlphaGo Developer”

I almost knew exactly who it was going to be when they mentioned AlphaGo Developer. For those who aren't that well versed in RL, I recommend watching his lectures at UCL ( [this video] ). Really clear explanations that went hand in hand when I was reading Sutton and Barto's introductory book.

Strong rec briandw · 2025-06 · on “Q-learning is not yet scalable”

This papers assumes that you know quite a bit about RL already. If you really want to dig into RL, this intro course from David Silver (Deep Mind) is excellent: [this video]

Recommends deepnet · 2017-03 · on “Ask HN: Best books on AI?”

Sutton & Barto's Reinforment Learning complete this triumvirate [LINK] David Silver's Reinforcement Course is based on Sutton & Barto [this video]

Recommends magoghm · 2017-12 · on “Mastering Chess and Shogi by Self-Play with General Reinforcement Learning”

You can check this Reinforcement Learning Course by David Silver on YouTube: [this video] By the way, I believe David Silver was the lead programmer for AlphaZero.

Recommends igravious · 2018-01 · on “Ask HN: Best introductory video courses on ML and Deep Learning?”

fast.ai Making neural nets uncool again. fast.ai is dedicated to making the power of deep learning accessible to all.[0] Udacity. Intro to Machine Learning: Pattern Recognition for Fun and Profit[1] MIT 6.S099: Artificial General Intelligence[2] Lecture Series on Artificial Intelligence by Prof. P. Dasgupta, Department of Computer Science & Engineering, Indian Institute of Technology, Kharagpur[3] DeepMind. Reinforcement Learning Course by David Silver[4] Stanford Winter Quarter 2016 class: CS231n: Convolutional Neural Networks for Visual Recognition.[5] [0] [LINK] [1] [LINK] [2] [LINK] [3] [LINK] [4] [this video] [5] [LINK]

Recommends crisbal_ · 2018-05 · on “Reinforcement Learning – Bandit Problems”

As someone who is doing his bachelor thesis on Reinforcement Learning this is some useful information. OT (but not really) question: does anyone here use Reinforcement Learning techniques at work? For the thesis I am working on black-box optimization of 2 variable functions with Reinforcement Learning (and comparing it with Bayesian Optimization techniques). As someone else suggested the Sutton & Barto book is really great knowledge but I would also like to suggest these lessons ( [this video] ) by David Silver (who worked on AlphaGo)

Recommends visarga · 2018-11 · on “Philosophy Has Made Plenty of Progress”

The notions of agent, environment and reward are encountered in Reinforcement Learning which is a sub-field of ML but also relevant to biological agents. There is a great RL course on YouTube by David Silver (one of the creators of AlphaGo, which is probably the most famous application of RL so far). [this video] The course can properly set the perspective of RL and shed new light on the philosophy of mind, if you take what it says and then extrapolate to humans and other agents. What I find fascinating about RL is that it can be defined concretely. Consciousness can only be defined by reference to other words, in a less exact and concrete way. RL can also explain how meaning appears, based on fu

Recommends alkhatib · 2019-02 · on “Dopamine framework: Fast prototyping of reinforcement learning algorithms (2018)”

I came across this a few days ago: For Reinforcement Learning specifically, the standard text is Reinforcement Learning: An Introduction[1]. Dave's UCL Course on RL[2] is great too (playlist of all lectures)[3]. Source: Julian Schrittwieser works on Deepmind at Google [LINK] [1] [LINK] [2] [LINK] [3] [this video]