Swarm intelligence can be defined as the study of the social insect metaphor for solving problems in computer science or engineering . It is a very powerful idea and a very interesting topic of research.
In this chapter, we study some of the ideas involved in the subject. We start by discussing the evolution of swarm intelligence and swarm-based robotics. We continue by discussing the necessity of the representation of the environment. Thereafter, we introduce the concept of personality traits as applied to swarm-based robotics.
6.2 The Evolution of Swarm Intelligence
Swarm intelligence grew out of the observation of social insect colonies. It emphasizes the distributedness and direct or indirect interaction among (relatively) simple agents . The approach is also designed to be flexible and robust, because a large number of agents will make the whole system resistant to individual failures.
The first and main application of swarm intelligence is in combinatorial optimization. It may be thought of as an alternative to classical approaches and, more specifically, genetic programming. Thus, it is also successfully applied to communication networks . A more exciting approach is the trial of achieving artificial intelligence based on simple agents—a type of collective intelligence. In this sense, intelligence is perceived as the capacity of solve problems and not pure rationality.