Emergence of adaptive behavior by chaotic neural networks
Ikuo Suzuki, Hiroshi Yokoi, Yukinori Kakazu · 2004
In this paper, we propose an emergent system in which an autonomous mobile robot can acquire environment oriented behavior. In the general robotic engineering, a system designer gave the model of environment and sensory-motor commands beforehand. However, we think that the autonomous robot has to be developed through the interaction between robot's behavior and the environmental information by itself. So, we construct the controller for the autonomous robot to acquire the adaptive behavior with the chaotic neural networks (CNNs). Furthermore, we make use of the dynamic learning method (DLM) as an on-line learning method. The results of the computational experiments show the chaotic search of this network plays an important role for the acquisition of the adaptive behavior.