Shypd.aiThe largest open index of AI toolsSimple_Reinforcement_Learning is an open-source toolkit that facilitates the development and testing of reinforcement learning algorithms. It supports Python 3.9, PyTorch 1.12.1, and Gym 0.26.2.
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Simple_Reinforcement_Learning is an open-source toolkit designed for the development and testing of reinforcement learning algorithms. It provides a structured environment for implementing various RL techniques, including stateless problems, Markov Decision Processes, dynamic programming, temporal difference algorithms, DynaQ, DQN, policy gradient, Actor-Critic, PPO, DDPG, SAC, imitation learning, offline learning, MPC, MBPO, goal-oriented reinforcement learning, and multi-agent systems. The toolkit is built to run on Python 3.9, PyTorch 1.12.1, and Gym 0.26.2, making it compatible with widely used machine learning libraries and environments. It serves as a valuable resource for researchers and engineers looking to explore and experiment with different reinforcement learning paradigms.
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