Roli Andrea, Ligot Antoine, Birattari Mauro
Department of Computer Science and Engineering, Campus of Cesena, Alma Mater Studiorum Università di Bologna, Bologna, Italy.
IRIDIA, Université libre de Bruxelles, Brussels, Belgium.
Front Robot AI. 2019 Nov 26;6:130. doi: 10.3389/frobt.2019.00130. eCollection 2019.
Complexity measures and information theory metrics in general have recently been attracting the interest of multi-agent and robotics communities, owing to their capability of capturing relevant features of robot behaviors, while abstracting from implementation details. We believe that theories and tools from complex systems science and information theory may be fruitfully applied in the near future to support the automatic design of robot swarms and the analysis of their dynamics. In this paper we discuss opportunities and open questions in this scenario.
总体而言,复杂性度量和信息论指标最近引起了多智能体和机器人领域的关注,这是因为它们能够捕捉机器人行为的相关特征,同时又能从实现细节中抽象出来。我们相信,复杂系统科学和信息论的理论与工具在不久的将来可能会得到有效应用,以支持机器人集群的自动设计及其动力学分析。在本文中,我们将探讨这种情况下的机遇和开放性问题。