Shypd.aiThe largest open index of AI toolsReinforcement-Learning-Papers is an Open Source tool that curates a list of research papers related to reinforcement learning. It includes both classic and recent papers from top conferences, primarily focusing on single-agent reinforcement learning.
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Reinforcement-Learning-Papers is an open-source GitHub repository that serves as a curated collection of research papers in the field of reinforcement learning. It encompasses both foundational classic papers and the latest research presented at top conferences such as ICLR, ICML, and NeurIPS. The collection primarily focuses on single-agent reinforcement learning, offering a structured overview of various topics including Model-Free (Online) RL, Model-Based (Online) RL, Offline RL, Meta RL, Adversarial RL, and RL with Transformer/LLM. This resource is invaluable for researchers, academics, and students who need to stay updated on significant advancements and foundational concepts in reinforcement learning.
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