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Ppo LunarLander V2
Model Overview
該模型使用Proximal Policy Optimization (PPO)算法訓練，旨在控制航天器在月球表面安全著陸。
Model Features
穩定訓練
使用PPO算法確保訓練過程的穩定性
連續動作空間處理
能夠處理LunarLander環境中的連續動作空間
獎勵優化
通過強化學習優化航天器著陸的獎勵函數
Model Capabilities
航天器控制
連續動作決策
強化學習任務解決
Use Cases
航天模擬
月球著陸器控制
模擬控制航天器在月球表面安全著陸的過程
平均獎勵達到92.08 +/- 122.82
教育演示
強化學習教學案例
作為強化學習算法的教學演示案例
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