Shypd.aiThe largest open index of AI toolsdeep-reinforcement-learning-papers is an open-source resource that curates a list of papers and materials dedicated to deep reinforcement learning. It serves as a valuable reference for researchers and practitioners in the field.
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deep-reinforcement-learning-papers is a comprehensive, open-source GitHub repository dedicated to cataloging papers and resources related to deep reinforcement learning. The collection is organized into categories such as Deep Value Function, Deep Policy, Deep Actor-Critic, Deep Model, and Application to Non-RL Tasks, making it easier for users to navigate specific areas of interest. It also includes sections for talks, slides, and other miscellaneous resources. The project is actively maintained with a stated goal to continuously add more papers and improve classification methods, welcoming contributions from the community. This resource is ideal for anyone looking to explore the foundational and cutting-edge research in deep reinforcement learning.
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