Swarm Intelligence (SI) is a computational intelligence technique involving the study of collective behavior in decentralized systems. Such systems are made up by a population of simple individuals interacting locally with one other and with their environment. Although there is typically no centralized control dictating the behavior of the individuals, local interactions among individuals often cause a global pattern to emerge. Examples of systems like this can be found in nature, including ant colonies, bird flocking, animal herding, honey bees, and many more.
Authors are invited to submit their original and unpublished work related to swarm intelligence, including research, theory, development, and applications. Areas of focus include particle swarm optimization, ant colony optimizations, cultural algorithms, swarm robotics, and other swarm-related topics. Included are models and analysis of collective behavior in natural societies; design, control, and optimization of collective artificial systems; and, applications of swarm intelligence principles to real-world problems.
Topics of interest:
Authors are invited to submit their original and unpublished work in the areas including, but not limited to, the following:
* Modeling and analysis of particle swarm optimization, ant colony optimization, culture algorithm, swarm robotics.
* Optimization techniques in dynamic, multi-objective, constrained environment
* Modeling and analysis of biological collective systems such as social insects colonies, school and flocking vertebrates
* Distributed computing, data clustering, graph partitioning, and decision making based on swarm intelligence principles
* Theory and practice of swarm intelligence in control system, power system, bioinformatics, business and finance, supply-chain management, transportation systems, and others areas
