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Evolutionary robotics : a tool to understand and design collective behaviours in collective adaptive systems
Collective adaptive systems are ubiquitous : from the many examples that can be observed in nature to artificial systems such as collective robotics or self-adaptive distributed algorithms. In this talk, I will describe two of our recent works on adaptive mechanisms in collective systems. Firstly, I will provide some insights related to the evolution of mutualistic cooperation in natural systems, using evolutionary robotics as a methodological tool to extend game theoretical models of cooperative hunting (work published in Plos Computational Biology). Secondly, I will address the problem of on-line distributed learning of behavioural specialisation in a robot swarm, for which evolutionary robotics stands as a promising, but currently limited, design method (work published in Frontiers in AI and Robotics). I will also briefly describe some other works related to the possible application of collective adaptive artificial systems, including the design of a micro-scale robot swarm.