SeanShih/REINFORCE-CartPole-v1

Reinforce Agent playing CartPole-v1

This is a trained model of a Reinforce agent playing CartPole-v1 . Portable weights: model_state_dict.pt. Define the matching Unit 4 Policy (CartPole: two layers; PixelCopter: three layers), instantiate it with state_space, action_space, and h_size from hyperparameters.json, then use policy.load_state_dict(torch.load(weights_path, map_location="cpu", weights_only=True)). The legacy model.pt contains a full Python model and requires its matching class. To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction