用递归神经网络控制障碍物场中物体的运动

A. Lyakhov, D. Korolev
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引用次数: 0

摘要

考虑递归神经网络控制模型,利用递归神经网络在有障碍物的场地上运动物体。通过遗传算法创建两个复杂度不同的神经网络。对每个神经网络描述强化学习算法。他们工作效率的比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Controlling the Movement of an Object on a Field with Barrier Using a Recurrent Neural Network
Consider control model recurrent neural network moving object on a field with barrier using a recurrent neural network. Via genetic algorithm create two neural network different complexity. For each neural network describe algorithm reinforcement learning. Comparison of the effectiveness of their work.
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