This repository presents a reinforcement learning (RL) solution based on the Double Deep Q-Network (DDQN) method within the Robot Operating System (ROS) framework, aimed at the challenging task of balancing a pole. Using the DDQN algorithm, the agent learns to balance a pole attached to a cart.
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This repository presents a reinforcement learning (RL) solution based on the Double Deep Q-Network (DDQN) method within the Robot Operating System (ROS) framework, aimed at the challenging task of balancing a pole. Using the DDQN algorithm, the agent learns to balance a pole attached to a cart.
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patweatharva/ROS_CartPole_DDQN
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This repository presents a reinforcement learning (RL) solution based on the Double Deep Q-Network (DDQN) method within the Robot Operating System (ROS) framework, aimed at the challenging task of balancing a pole. Using the DDQN algorithm, the agent learns to balance a pole attached to a cart.
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