In Lecture 14 we move from supervised learning to reinforcement learning (RL), in which an agent must learn to interact with an environment in order to maximize its reward. We formalize reinforcement learning using the language of Markov Decision Processes…

This brief article takes a quick look at working with OpenAI Gym with Scala as well as explores the design of the API and gives some HTTP commands.

We introduce TensorFlow Agents, an efficient infrastructure paradigm forbuilding parallel reinforcement learning algorithms in TensorFlow. We simulatemultipl...

Full episode with David Silver (Apr 2020): https://www.youtube.com/watch?v=uPUEq8d73JI
Clips channel (Lex Clips): https://www.youtube.com/lexclips
Main channel (Lex Fridman): https://www.youtube.com/lexfridman
(more links below)

Podcast full episodes playlist:…

❤️ Check out Weights & Biases and sign up for a free demo here: https://wandb.com/papers
❤️ Their mentioned post is available here: https://colab.research.google.com/drive/1gKixa6hNUB8qrn1CfHirOfTEQm0qLCSS

📝 The paper "Improving Playtesting Coverage via…

Open source code for AlphaFold 2. Contribute to google-deepmind/alphafold development by creating an account on GitHub.

The stochastic multi-armed bandit (MAB) is a benchmark model for decision-making under uncertainty. MABs are used in a wide range of applications, from Internet advertising to healthcare. Now, new research has suggested that algorithms for MAB problems that…

Recent years have witnessed significant advancements in offline reinforcement learning (RL), resulting in the development of numerous algorithms with varying degrees of complexity. While these...