Flocks of birds, shoals of fish, colonies of ants, various types of vegetation – nature knows how to combine simple small components to large systems with amazing capabilities. In contrast to technical systems, natural systems are distributed and self-organizing. They are very tolerant on losing one or more components. Lakeside Labs aims at getting the concept of self-organization integrated into technical systems.
Though we can list numerous natural and social examples of self-organization, there is no straightforward method for designing and testing how microscopic rules influence macroscopic behavior in an artificial self-organizing system. “It is very difficult to predict how changing a certain parameter will effect the whole system,” states Wilfried Elmenreich. In order to solve this problem, the team experiments with biologically inspired methods, such as evolutionary computation.
A major result of this research is the freely available software tool FREVO, which relieves engineers from making low-level design decisions and enables them to concentrate on design. “The idea is to create a piece of software simplifying the design process,” says researcher István Fehérvári about the tool which has continuously been improved. “In the past we successfully evolved selforganizing behavior for a team of robots playing soccer or cooperatively observing a given area and even behavioral patterns for social simulations.”
Evolution as a tool to design self-organizing systems
Lecture Notes in Computer Science on Self-Organizing Systems, 2014
Self-organization in communication networks: Principles and design paradigms
IEEE Communications Magazine, 2005