Arbeitsgruppe Gros

Robotchaosgradient

Prof. Dr. Claudius Gros

Computational Neurosciences

All thinking occurring in the brain is carried out by a highly complex and continuously evolving network of interacting neurons. In this context we develop theories for synaptic learning, i.e. for the formation of memories, which are based on information-theoretical principles. Of special interest is here the (meta-) dynamics of the attracting states guiding the neural dynamics during decision-making processes.

Complex Systems Theory

We study the emergence of partially predictable chaos in classical dynamical systems, in autonomously active neural networks and in the context of attracting states in the sensorimotor loop (the feedback loop of brain, body and environment). Model building goes in this field hand in hand with numerical simulations of the defining equation of motions and of self-organized robots in a physical simulation environment.

Email: gros07@itp.uni-frankfurt.de