The special issue will explore new approaches and perspectives of swarm intelligence algorithms and applications. It intends to collect a series of leading and cutting-edge articles on ideas, concepts, and technologies that make use of swarm intelligence in all walks of research fields.

Swarm intelligence (SI) is based on collective behavior of self-organized systems. Typical swarm intelligence schemes include particle swarm optimization (PSO), ant colony system (ACS), stochastic diffusion search (SDS), bacteria foraging (BF), the bees algorithm, swarm robotics, etc. Besides the applications to conventional optimization problems, SI can be used in controlling robots and unmanned vehicles, predicting social behaviors, enhancing the telecommunication and computer networks, etc. Indeed, the use of swarm optimization can be applied to a variety of fields in engineering and social sciences.

The objective of the special issue is to provide original contributions, and to review and survey research and development in applications of swarm intelligence (SI), focusing on state-of-the-art and potential future technologies and providing a good starting point for individuals entering these active research areas.

Topics will include, but not limited to, the follows:
 applications of swarm intelligence techniques, including
• data clustering,
• design optimization,
• job scheduling,
• multimedia content protection,
• multi-objective optimization,
• pattern recognition,
• robotics, and
• other relating applications;
 new algorithms addressing the problem of swarm intelligence;
 comparisons of techniques and performance of various swarm intelligence algorithms;
 theoretical analysis for swarm intelligence, and
 other relating research topics to swarm intelligence.