Shypd.aiThe largest open index of AI toolsDeep-Reinforcement-Learning-Algorithms is an open-source collection of 32 projects implementing various deep reinforcement learning algorithms. It includes detailed training logs for algorithms like Q-learning, DQN, PPO, DDPG, TD3, SAC, and A2C.
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Deep-Reinforcement-Learning-Algorithms is a comprehensive open-source repository featuring 32 distinct projects focused on deep reinforcement learning methods. Each project is designed to solve specific environments using various algorithms such as Q-learning, DQN, PPO, DDPG, TD3, SAC, and A2C. The collection is structured to demonstrate how different models interact with diverse environments, with some environments being solved by multiple algorithms for comparative study. All projects are presented as Jupyter notebooks, complete with detailed training logs, making it an invaluable resource for learning, experimenting, and understanding the practical application of deep reinforcement learning concepts. It covers topics from Monte-Carlo methods to advanced Actor-Critic approaches.
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