Chaotic itinerancy in coupled dynamical recognizers.
We argue that chaotic itinerancy in interaction between humans originates in the fluctuation of predictions provided by the nonconvergent nature of learning dynamics. A simple simulation model called the coupled dynamical recognizer is proposed to study this phenomenon. Daily cognitive phenomena provide many examples of chaotic itinerancy, such as turn taking in conversation. It is therefore an interesting problem to bridge two chaotic itinerant phenomena. A clue to solving this is the fluctuation of prediction, which can be translated as "hot prediction" in the context of cognitive theory. Hot prediction is simply defined as a prediction based on an unstable model. If this approach is correct, the present simulation will reveal some dynamic characteristics of cognitive interactions.
Ikegami
Takashi
T
Department of General Systems Sciences, The Graduate School of Arts and Sciences, University of Tokyo, 3-8-1 Komaba, Tokyo 153-8902, Japan.
Morimoto
Gentaro
G
D003071:Cognition; D006801:Humans; D007802:Language; D007858:Learning; D008568:Memory; D008959:Models, Neurological; D015233:Models, Statistical; D009415:Nerve Net; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D013997:Time Factors