Aggregation is one of the most widespread phenomena in animal groups and often represents a collective dynamic response to environmental conditions. In social species the underlying mechanisms mostly obey self-organized principles. This phenomenon constitutes a powerful model to decouple purely social components from ecological factors. Here we used a model of cockroach aggregation to address the problems of sensitivity of collective patterns and control of aggregation dynamics. The individual behavioural rules (as a function of neighbour density) and the emergent collective patterns were previously quantified and modelled by Jeanson et al. (2003, 2004). We first present the diverse spatio-temporal patterns of a derived model in response to parameter changes, either involving social or non-social interactions. This sensitivity analysis is then extended to evaluate the evolution of these patterns in mixed societies of sub-populations with different behavioural parameters. Simple linear or highly non-linear collective responses emerge. We discuss their potential application to control animal populations by infiltration of biomimetic autonomous robots that mimic cockroach behaviour. We suggest that detailed behavioural models are a prerequisite to do so.
2010. Semi-automatic behavior analysis using robot/insect mixed society and video tracking. Journal of Neuroscience Methods 191:1 ► pp. 138 ff.
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