Hans H. Diebner:

A Simulating Cognitive System with Adaptive Capability (pdf)

BioSystems 64/1-3, 141-147 (2002)


Dedicated to the memory of Michael Conrad, this paper builds on his seminal ideas expressed in his famous book "Adaptability" as well as in his later works. We investigate a recently published adaptive system for the instantaneous recognition of dynamics with respect to its adaptability to the Lorenz system. The system consists of a pool of internal dynamical elements. These elements are defined through a set of parameter values that encode for a specific dynamics behavior. If now the system is faced with an unknown external dynamics - unknown with respect to the parameter - it is capable not only to recognize the dynamics but also to adapting to the correct dynamics which in turn leads to a simulation capability. The system impressively quickly follows sudden qualitative changes of the external dynamics. The adaptation works even quicker when the correct dynamics is already represented within the internal pool. This leads to the idea of memorizing the represented dynamics within the pool, whereby the elements that correspond to rarely externally presented dynamics can be given free for the adaptation and memorization of more frequently presented dynamics.

Related publications:

Hans H. Diebner, Sven Sahle and Axel A. Hoff: A Realtime Adaptive System for Dynamics Recognition. Chaos, Solitons & Fractals 13/4, 781-786, (2002). (pdf)

Hans H. Diebner, Axel A. Hoff, Adolf Mathias, Horst Prehn, Marco Rohrbach and Sven Sahle: Towards a Second Cybernetics Model for Cognitive Systems. Chaos, Solitons & Fractals 13/7, 1465-1474, (2002). (pdf)

Hans H. Diebner, Axel A. Hoff, Adolf Mathias, Horst Prehn, Marco Rohrbach and Sven Sahle: Control and Adaptation of spatio-temporal patterns. Z. Naturforsch.56a, 663-661 (2001).

Hans H. Diebner and Peter Weibel: Stimulus Meets Simulus - Thoughts on the Interface. Telematik 8, 45-50 (1/2002).

Hans H. Diebner and Florian Grond: Usability of Synchronization for Cognitive Modeling. Chaos, Solitons & Fractals 25, 905-910 (2005). (pdf)