Intelligent Systems 

Discussion group on Entropy and Self-organisation in Multi-Agent Systems

Sensor Networks,  Small Worlds,  Scale-free Networks

Albert-Laszlo Barabasi and Reka Albert. Emergence of Scaling in Random Networks. Science, October 1999.

      Abstract. Systems as diverse as genetic networks or the World Wide Web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature was found to be a consequence of two generic mechanisms: (i) networks expand continuously by the addition of new vertices, and (ii) new vertices attach preferentially to sites that are already well connected. A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.

Duncan J. Watts & Steven H. Strogatz. Collective dynamics of ‘small-world’ networks. Nature 393, 1998.

      Abstract. Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them ‘small-world’ networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation). The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration
graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. ...

Contact:

Dr Mikhail Prokopenko
Tel : 61 (02) 9325 3264
Fax: 61 (02) 9325 3200
mikhail.prokopenko@csiro.au