Swarm intelligence is the discipline studying how individuals can coordinate their behaviors in a decentralized and self-organized manner, so as to exhibit complex collective behavior. Swarm-intelligent systems are made of large numbers of individuals that tend to interact with each other in simple ways. Swarm-intelligent systems are common throughout nature. Examples are bacteria colonies, neural networks, social insects, and flocks/crowds of vertebrates. In addition, humans have produced a variety of (artificial) swarm systems, ranging from swarm-based optimization algorithms to sensor networks, swarms of robots, and smart materials. In each of these systems, populations of individuals change their spatiotemporal configuration based on local interactions with each other and the environment. A potential advantage of swarm-intelligent design is that it is (ideally) scale free; in other words, the individuals can be scaled up in numbers. Moreover, swarm-intelligent design tends to make systems inherently robust and flexible.
Since the foundation of this task force in 2002, the study of Swarm Intelligence has gained enormous momentum and become an inter-disciplinary field of research. As a result of this, it has become increasingly challenging to keep track of significant findings and identify promising avenues for future research.