BipedalWalker-RL

Public

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.

bipedalwalker-v3 gymnasium-environment openai ppo reinforcement-learning

Creat：2024-09-24T20:56:42

Update：2025-01-07T17:46:47

https://gymnasium.farama.org/environments/box2d/bipedal_walker/

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