Maturity of the Particle Swarm as a Metric for Measuring the Collective Intelligence of the Swarm

• http://link.springer.com/chapter/10.1007/978-3-642-38703-6_5

particle swarm optimization, maturity model, particle swarm collective intelligence

The particle swarm collective intelligence has been recognized as a tool for dealing with the optimization of multimodal functions with many local optima. In this article, a research work is introduced in which the cooperative Particle Swarm Optimization strategies are analysed and the collective intelligence of the particle swarm is assessed according to the proposed Maturity Model. The model is derived from the Maturity Model of C2 (Command and Control) operational space and the model of Collaborating Software. The aim was to gain a more thorough explanation of how the intelligent behaviour of the particle swarm emerges. It has been concluded that the swarm system is not mature enough because of the lack of the systems awareness, and that a solution would be some adaptation of particles behavioural rules so that the particle could adjust its velocity using control parameters whose value would be derived from inside of the swarm system, without tuning.

The particle swarm collective intelligence has been recognized as a tool for dealing with the optimization of multimodal functions with many local optima. In this article, a research work is introduced in which the cooperative Particle Swarm Optimization strategies are analysed and the collective intelligence of the particle swarm is assessed according to the proposed Maturity Model. The model is derived from the Maturity Model of C2 (Command and Control) operational space and the model of Collaborating Software. The aim was to gain a more thorough explanation of how the intelligent behaviour of the particle swarm emerges. It has been concluded that the swarm system is not mature enough because of the lack of the systems awareness, and that a solution would be some adaptation of particles behavioural rules so that the particle could adjust its velocity using control parameters whose value would be derived from inside of the swarm system, without tuning.