Swarm intelligence is the discipline that deals with natural and artificial systems composed of many individuals which coordinate their activities using decentralised control and self-organisation. In particular, the discipline focuses on collective behaviour resulting from local interactions of individuals with each other and with their environment.
Examples of systems studied within this discipline include colonies of ants and termites, schools of fish, flocks of birds and herds of land animals. Some human artefacts also fall into the domain of swarm intelligence, notably some multi-robot systems, and also certain computer programs which are written to tackle optimisation and data analysis problems.
The objective of this special issue is to bring researchers from academia and industry together to report and review the latest advances in this field, and to explore future directions.
Suitable topics include but are not limited to:
- Modelling of collective biological systems such as social insect colonies, flocking vertebrates and human crowds, as well as any other swarm intelligence systems
- Swarm-based optimisation for multi-objective optimisation problems
- Swarm-based optimisation for complex constrained optimisation problems
- Swarm-based optimisation for dynamic environment optimisation
- Hybrid swarm-based optimisation techniques
- Learning and search strategies in swarm-based optimisation
- Applications of swarm-based optimisation methodology, such as graph partitioning, data clustering, etc.
- Future directions of swarm-based systems
Submission deadline: 15 August, 2011
Acceptance notification: 20 October, 2011
Final version due: 20 December, 2011