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Reinforcment 7 by 2303a51228 is a document available to read on EtoBox.

The document presents a Python implementation of the REINFORCE algorithm using PyTorch and the Gymnasium library for reinforcement learning. It defines a policy network, computes returns, and trains the model over 1000 episodes on the CartPole-v1 environment, reporting average returns every 100 episodes. The results indicate improved performance over time, achieving an average return of 500.00 by the end of training.

Author
2303a51228
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EN