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BipedalWalker-RL

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This project implements agent training using the Proximal Policy Optimization (PPO) algorithm in the BipedalWalker-v3 environment at two difficulty levels: normal and hardcore. The model's performance is evaluated based on rewards collected during the training process.

Creat2024-09-24T20:56:42
Update2025-01-07T17:46:47
https://gymnasium.farama.org/environments/box2d/bipedal_walker/
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