Bio-inspired Mechanisms for Artificial Self-organised Systems

Self-organization is a growing interdisciplinary field of research about a phenomenon that can be observed in the Universe, in Nature and in social contexts. Research on self-organization tries to describe and explain forms, complex patterns and behaviours that arise from a collection of entities without an external organizer. As researchers in artificial systems, our aim is not to mimic selforganizing phenomena arising in Nature, but to understand and to control underlying mechanisms allowing desired emergence of forms, complex patterns and behaviours. Rather than attempting to eliminate such self-organization in artificial systems, we think that this might be deliberately harnessed in order to reach desirable global properties. In this paper we analyze three forms of self-organization: stigmergy, reinforcement mechanisms and cooperation. The amplification phenomena founded in stigmergic process or in reinforcement process are different forms of positive feedbacks that play a major role in building group activity or social organization. Cooperation is a functional form for selforganization because of its ability to guide local behaviours in order to obtain a relevant collective one. For each forms of self-organisation, we present a case study to show how we transposed it to some artificial systems and then analyse the strengths and weaknesses of such an approach.