Oct 15, 2018 · We discuss deep reinforcement learning in an overview style. We draw a big picture, filled with details. We discuss six core elements, six important mechanisms ...
Oct 15, 2018 · The manuscript introduces AI, machine learning, and deep learning briefly, and provides a mini tutorial for reinforcement learning.
This work discusses deep reinforcement learning in an overview style, focusing on contemporary work, and in historical contexts.
Publications · Iterative improvements from feedback for language models · Reinforcement Learning in Practice: Opportunities and Challenges · Guest editorial: ...
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This work discusses core RL elements, including value function, in particular, Deep Q-Network (DQN), policy, reward, model, planning, and exploration, ...
Sep 15, 2018 · This is a collection of resources for deep reinforcement learning, including the following sections: Books, Surveys and Reports, Courses, Tutorials and Talks, ...
RL, AI, LLMs, agent, code, blockchain. Guest editor, MLJ SI. Co-Chair for workshops in AAAI, ICML, NeurIPS. PhD @UAlberta.
Dec 30, 2018 · "Explore, Exploit, and Explode — The Time for Reinforcement Learning is Coming", Yuxi Li. DL, M, MF, D. r/reinforcementlearning - "Explore ...
Nov 24, 2023 · David Silver, Reinforcement Learning Course (classic) ; Reinforcement Learning: An Introduction (standard textbook) ; OpenAI Spinning up.
Nov 23, 2023 · An RL agent interacts with the environment over time to learn a policy, by trial and error, that maximizes the long-term, cumulated reward.