Swarms, Phase Transitions, and Collective Intelligence
arXiv:adap-org/9306002
Abstract
A spacially extended model of the collective behavior of a large number of locally acting organisms is proposed in which organisms move probabilistically between local cells in space, but with weights dependent on local morphogenetic substances, or morphogens. The morphogens are in turn are effected by the passage of an organism. The evolution of the morphogens, and the corresponding flow of the organisms constitutes the collective behavior of the group. Such models have various types of phase transitions and self-organizing properties controlled both by the level of the noise, and other parameters. The model is then applied to the specific case of ants moving on a lattice. The local behavior of the ants is inspired by the actual behavior observed in the laboratory, and analytic results for the collective behavior are compared to the corresponding laboratory results. It is hoped that the present model might serve as a paradigmatic example of a complex cooperative system in nature. In particular swarm models can be used to explore the relation of nonequilibrium phase transitions to at least three important issues encountered in artificial life. Firstly, that of emergence as complex adaptive behavior. Secondly, as an exploration of continuous phase transitions in biological systems. Lastly, to derive behavioral criteria for the evolution of collective behavior in social organisms.
1.25Mb uuencoded postscript file, 30 pages, 9 figs
Cited by in corpus (14)
- Self-Organized Stigmergic Document Maps: Environment as a Mechanism for Context Learning
- Artificial Ant Colonies in Digital Image Habitats - A Mass Behaviour Effect Study on Pattern Recognition
- KohonAnts: A Self-Organizing Ant Algorithm for Clustering and Pattern Classification
- Analysis of Aperture Evolution in a Rock Joint Using a Complex Network Approach
- On Self-Regulated Swarms, Societal Memory, Speed and Dynamics
- On Ants, Bacteria and Dynamic Environments
- The collective brain is critical
- Societal Implicit Memory and his Speed on Tracking Extrema over Dynamic Environments using Self-Regulatory Swarms
- Computational Chemotaxis in Ants and Bacteria over Dynamic Environments
- Emergent complexity: what uphill analysis or downhill invention can not do
- Social Cognitive Maps, Swarm Perception and Distributed Search on Dynamic Landscapes
- Meta-Structural properties in Collective phenomena
- Modelling Open-Source Software Reliability Incorporating Swarm Intelligence-Based Techniques
- Developing of New Facets of Indirect Modeling in the Geosciences