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Transparent Machine Education of Neural Networks for Swarm Shepherding Using Curriculum Design

机译:基于课程设计的群体管理神经网络的透明机器教育

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Swarm control is a difficult problem due to the need to guide a large number of agents simultaneously. We cast the problem as a shepherding problem, similar to biological dogs guiding a group of sheep towards a goal. The shepherd needs to deal with complex and dynamic environments and make decisions in order to direct the swarm from one location to another. In this paper, we design a novel curriculum to teach an artificial intelligence empowered agent to shepherd in the presence of the large state space associated with the shepherding problem and in a transparent manner. The results show that a properly designed curriculum could indeed enhance the speed of learning and the complexity of learnt behaviours.
机译:群体控制是一个难题,因为需要同时引导大量的特工。我们把这个问题看作是一个牧羊人的问题,类似于将一群绵羊引导到一个目标的生物狗。牧羊人需要应对复杂而动态的环境,并做出决策,以便将种群从一个地点引导到另一个地点。在本文中,我们设计了一种新颖的课程,在具有与牧羊犬问题相关联的大型状态空间的情况下,以透明的方式教授由人工智能授权的牧羊犬。结果表明,设计合理的课程确实可以提高学习速度和学习行为的复杂性。

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