Ikegami Takashi, Morimoto Gentaro
Department of General Systems Sciences, The Graduate School of Arts and Sciences, University of Tokyo, 3-8-1 Komaba, Tokyo 153-8902, Japan.
Chaos. 2003 Sep;13(3):1133-47. doi: 10.1063/1.1602991.
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.
我们认为，人类之间互动中的混沌游移源于学习动力学的非收敛性所提供预测的波动。为研究这一现象，我们提出了一个名为耦合动力学识别器的简单模拟模型。日常认知现象提供了许多混沌游移的例子，比如对话中的轮流发言。因此，连接两种混沌游移现象是一个有趣的问题。解决这个问题的一个线索是预测的波动，在认知理论的背景下，这可以被翻译为“热预测”。热预测简单定义为基于不稳定模型的预测。如果这种方法是正确的，那么当前的模拟将揭示认知互动的一些动态特征。
