DQN-using-PyTorch和ML-Agents:如何使用PyTorch和ML-Agents环境实现基于矢量的DQN的简单示例-源码

上传者: 42154650 | 上传时间: 2021-04-10 16:10:27 | 文件大小: 2.72MB | 文件类型: ZIP
使用PyTorch和Unity ML-Agent进行深度Q网络(DQN)强化学习 一个简单的示例,说明如何使用PyTorch和ML-Agents环境实现基于矢量的DQN。 深度强化学习(DRL)中的Udacity Danaodgree项目 该存储库包含以下与DQN相关的文件: dqn_agent.py-> dqn-agent实现 replay_memory.py-> dqn-agent的重播缓冲区实现 model.py->用于基于向量的DQN学习的示例PyTorch神经网络 train.py->初始化并实施DQN代理的训练过程。 test.py->测试受过训练的DQN代理 根据Udacit

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