Social Adaptation of Robots for Modulating Self-Organization in Animal Societies

Author(s):  
Payam Zahadat ◽  
Michael Bodi ◽  
Ziad Salem ◽  
Frank Bonnet ◽  
Marcelo Elias De Oliveira ◽  
...  
1999 ◽  
Vol 354 (1388) ◽  
pp. 1395-1405 ◽  
Author(s):  
Ana B. Sendova-Franks ◽  
Nigel R. Franks

The prospect of generic principles of biological organization being uncovered through the increasingly broad use of the concepts of ‘self–assembly’ and ‘self–organization’ in biology will only be fulfilled if students of different levels of biological organization use the same terms with the same meanings. We consider the different ways the terms ‘self–assembly’ and ‘self–organization’ have been used, from studies of molecules to studies of animal societies. By linking ‘self–assembly’ and ‘self–organization’ with division of labour, we not only put forward a distinction between the underlying concepts but we are also able to relate them to the question: Why has a certain structure been favoured by natural selection? Using the particularly instructive case of social resilience in ant colonies, we demonstrate that the principle of self–organizing self–assembly may apply to higher levels of biological organization than previously considered. We predict that at the level of interactions among organisms within the most advanced animal societies, specialization through learning has a crucial role to play in re–assembly processes. This review may also help important commonalities and differences to be recognized between ordering mechanisms up to the social level and those further up the biological hierarchy, at the level of ecological communities.


Author(s):  
D.J.T Sumpter

In recent years, the concept of self-organization has been used to understand collective behaviour of animals. The central tenet of self-organization is that simple repeated interactions between individuals can produce complex adaptive patterns at the level of the group. Inspiration comes from patterns seen in physical systems, such as spiralling chemical waves, which arise without complexity at the level of the individual units of which the system is composed. The suggestion is that biological structures such as termite mounds, ant trail networks and even human crowds can be explained in terms of repeated interactions between the animals and their environment, without invoking individual complexity. Here, I review cases in which the self-organization approach has been successful in explaining collective behaviour of animal groups and societies. Ant pheromone trail networks, aggregation of cockroaches, the applause of opera audiences and the migration of fish schools have all been accurately described in terms of individuals following simple sets of rules. Unlike the simple units composing physical systems, however, animals are themselves complex entities, and other examples of collective behaviour, such as honey bee foraging with its myriad of dance signals and behavioural cues, cannot be fully understood in terms of simple individuals alone. I argue that the key to understanding collective behaviour lies in identifying the principles of the behavioural algorithms followed by individual animals and of how information flows between the animals. These principles, such as positive feedback, response thresholds and individual integrity, are repeatedly observed in very different animal societies. The future of collective behaviour research lies in classifying these principles, establishing the properties they produce at a group level and asking why they have evolved in so many different and distinct natural systems. Ultimately, this research could inform not only our understanding of animal societies, but also the principles by which we organize our own society.


1994 ◽  
Vol 39 (9) ◽  
pp. 916-916
Author(s):  
Terri Gullickson

2013 ◽  
Author(s):  
Yohanes Kartika Herdiyanto ◽  
David Hizkia Tobing ◽  
I. Putu Galang Dharma Putra ◽  
Anak Agung Ketut Sri Wiraswati

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