Chair of Computational Intelligence

Our major focus in research and teaching is on Computational Intelligence (CI) algorithms for decision-making problems such as Multi-objective Optimisation, Evolutionary Algorithms, Swarm Intelligence, Evolutionary Robotics, and Swarm Robotics. Our goal is to develop new methodologies for better, more efficient, and, above all, informed decisions.

Computational Intelligence is an important tool for dealing with complex systems and can be applied across many domains: the automotive industry, medical applications, computational chemistry, geology, entrepreneurship, system design, games, biology, etc. In this area, we work on CI algorithms and their applications to multi-objective problems.

Furthermore, we investigate applications of Swarm Intelligence algorithms in swarm robotics at SwarmLab. Swarm Intelligence is a collective learning mechanism with the goal of achieving complex and intelligent global behavior using simple rules on simple technical devices. Given the progress in the development of technical systems, Swarm Intelligence is becoming increasingly popular. Technical systems are becoming smaller, low-cost, powerful, and distributed everywhere. Examples of such systems include sensor networks, computing resources, and mobile devices such as micro-robots and smart objects, to which we can apply swarm intelligence to achieve desired and intelligent behavior.

Take a closer look at our research blog, CI BLOG, for more details about our recent research. 

Our research is financially spported by