A measure of heterogeneity in multi-agent systems
A measure of heterogeneity in multi-agent systems
复制标题
多智能体系统中异质性的度量
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
M. Egerstedt
中科院分区：
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作者：
P. Twu;Yasamin Mostofi;M. Egerstedt
以前已经研究和部署了异质多智能体系统来解决许多不同的任务。尽管如此，我们仍然对“异质性”到底是什么缺乏基本的理解。例如，是什么使一个代理团队比另一个团队更具异构性？在本文中，我们通过提出异质性的度量来解决这个问题。通过结合不同的熵概念，这种测量既考虑了系统的复杂性，又考虑了系统的差异。其结果是一个既容易计算又有直观意义的公式。概述了生物学、经济学和机器人等不同领域中现有的多样性衡量标准，并讨论了它们的相对优点和缺点。我们展示了我们提出的异构性度量如何克服先前度量中发现的问题。最后，我们讨论了如何通过使用公共任务空间的概念来比较具有不同能力的代理，从而将新的异构性度量具体应用于多代理系统。
Heterogeneous multi-agent systems have previously been studied and deployed to solve a number of different tasks. Despite this, we still lack a basic understanding of just what “heterogeneity” really is. For example, what makes one team of agents more heterogeneous than another? In this paper, we address this issue by proposing a measure of heterogeneity. This measure takes both the complexity and disparity of a system into account by combining different notions of entropy. The result is a formulation that is both easily computable and makes intuitive sense. An overview is given of existing metrics for diversity found in various fields such as biology, economics, as well as robotics, followed by a discussion of their relative merits and demerits. We show how our proposed measure of heterogeneity overcomes problematic issues identified across the previous metrics. Finally, we discuss how to apply the new measure of heterogeneity specifically to multi-agent systems by using the notion of a common task-space to compare agents with different capabilities.