导弹模型matlab代码-deep_meta-learning_guidance_law:论文代码:“学习指南:基于深度元学习和模型预测路径积

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导弹模型matlab代码学习指南:基于深度元学习和模型预测路径积分控制的制导律 关于 这项工作的目的是利用本文所述的导弹制导问题,利用模型预测路径积分控制器实施基于模型的深度强化学习,该IEEE Access论文位于arXiv上,并且在arXiv上也可用。 依存关系 此代码已经在python上进行了测试,并且需要安装tensorflow-gpu和numpy。 该演示运行建立在预先训练的指导神经网络模型的基础上,如果有人提出要求,其代码,系统模型和训练数据集将在之后发布。 怎么跑 请使用mppi_run.py运行。 也可以使用monte_carlo_simu.sh进行迭代运行以获取蒙特卡洛采样结果。 在本文中,使用MATLAB的get_Monte.m文件收集了蒙特卡洛模拟的结果。 引用 如果您发现我们的作品对您的研究有用,请考虑引用: @article{liang2019learning, title={Learning to Guide: Guidance Law Based on Deep Meta-Learning and Model Predictive Path Integra

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