This category is dedicated to several scientific fields I am interested in and therefore would like to introduce in a vivid way. This includes, of course, projects of my own.

Artificial Life is a scientific field, which does not cut systems apart to shed light on how they work (Top-Down approach). Insteads, it models system parts and, out of these, the system as a whole(Bottom-Up). It is even possible to grow artificial systems.

Optimization Strategies allow for finding plausible solutions solving difficult problems. Some bio-inspired of these are presented in this section as well as application examples.

In biology, behavior of swarms consisting of many individuals is often recognized to be more than the sum of its parts. Just by local interactions of simple individuals, complex behavior emerges on macro-level. Those kinds of behavior can not only be observed in nature, but are also synthesized.

Summary of my diploma thesis (equiv. master's thesis). Using many computers in parallel, I simulated entire, small ecologies to make swarms of artificial living beings evolve. A fascinating variety of behavior patterns also known from biology was elicited.

Neural Networks are a mechanism inspired by nature, that simulates small brains and enables computers to learn in a bio-inspired way and even generalize solutions to problem instances.

In this section, you can also find my manuscript “A Brief Introduction of Neural Networks”.

Information and coverage about the RoboCup World Championships 2009 in Graz, Austria.

This page gives a brief summary of my project at Cornell University in 2007. Minimalistic designed robots, that are even unable to steer at individual level, evolve full navigational capabilities as a swarm.