Cybernetic machines: Complexity of modular neurodynamics

  • Frank Pasemann (Fraunhofer Institute for Autonomous Intelligent Systems, Sankt Augustin)
A3 02 (Seminar room)


Following the Artificial Life approach to Evolutionary Robotics the goal of Neurocybernetic Machines is to test hypotheses on the possible realization of artificial cognitive systems. In this context a modular neurodynamics approach to cognition is adopted, which should lead to a bottom up development of larger systems with more and more comprehensive abilities. Since the ability to categorize the features and effects of the real world in behavior relevant terms a rich reservoir of attractors is essential. A reasonable complexity measure for the attractor structure of a neuromodule should help to set up rules for an effective coupling of such functionally segregated modules; effective here refers to what may be called an "emergent" neurodynamics. The modular neurodynamics approach is introduced and a topological complexity measure (R. Thom) is discussed.