Bipedal Walker using DQN
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Updated
Jun 26, 2024 - Python
Bipedal Walker using DQN
Reinforcement Learning and Deeep reinforcement Learning
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.
Teaching an bipedal bot how to walk using a TD3 algorithm (variant of Reinforcement Learning - Actor & Critic method)
PPO for Bipedal Walker
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