Groups of humans or animals often make decisions collectively without any central control or coordination. The paradigmatic example of self-organized groups are colonies of social insects, such as ants, termites, and (some species of) bees and wasps, whose strikingly organized and seemingly purposeful behavior at the group level is organized without any central "master plan". An ant colony's activities, such as coordinated attack when threatened or the building of complex trail networks, require elaborate coordination and decision making. Yet, despite the involvement of up to millions of individuals, there is no leader making the decisions: the complex behavior at the colony level emerges from simple interactions between myriads of individuals that only process local information.
Many aspects of self-organized phenomena in nature can be better understood from the viewpoint of information processing. Natural computation studies such phenomena as computational processes and uses information theory to explain their behavior.
Self-organized behavior exhibits a number of properties that are highly desirable in technical applications, specifically robustness, adaptiveness and parallelism. Hence, social insect behavior has been used as an inspiration for a wide range of engineering tasks. Among the most important examples of so-called "Swarm Intelligence" applications are ant colony optimization, a method for combinatorial optimization, swarm robotics and network routing.
We are specifically interested in the adaptiveness of self-organized systems, i.e. their ability to "reorganize" in order to adapt to a changing environment.
Our work is focused on theoretical aspects and mainly concerned with understanding real biological systems, in particular ant colonies and slime molds. We also use the insights gained from the study of self-organizing systems in biology to develop new solutions to computational problems, specifically self-organising algorithms for computationally hard combinatorial optimization problems.
This work is funded by the Australian Research Council and conducted in close collaboration with the Research Centre on Animal Cognition at the Universite Paul Sabatier (Toulouse), the Behavior and Genetics of Social Insects Lab and the Center for Mathematical Biology at the School of Biological Sciences, University of Sydney
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