# Off-Policy Learning

This is a deep reinforcement learning model based on the TQC algorithm, specifically designed for the PandaPickAndPlace-v1 environment, used for robotic arm grasping and placing tasks.

This is a reinforcement learning model based on the SAC algorithm, specifically designed for the Walker2d-v3 environment to control bipedal robot walking.

This is a DQN agent model trained using stable-baselines3, specifically designed to solve reinforcement learning tasks in the MountainCar-v0 environment.

This is a decision transformer model trained on medium-performance trajectories in the Gym Hopper environment, suitable for continuous control tasks.