Self-organizing system obtaining communication ability. Primitive model for language generation.
As one of the synthetic approaches to brain functions, the possibility is discussed that two intellectual robots could make "words" for themselves and come to communicate with each other. Associatron, a model for associative memory with a neural network structure, is used as the memory in the brain, and information from the outer world is accumulated in it. Concepts regarding objects and attributes are extracted from the stored information, where the Associatron properties are utilized. The robots give specific names to the concepts and interchange them with each other. When the robots have the same experience at the same time, they modify their own words according to what the other robot says. As they repeat common experiences, the differences between the words become smaller and smaller, and finally the robots agree on a word for each object. At this stage, the robots can exchange information with their words and each can act accordingly on the word from the other. This study shows that the self-organizing system with the above function can be constructed as a neural network model.
Nakano
K
K
Department of Mathematical Engineering and Information Physics, Faculty of Engineering, University of Tokyo, Japan.
Sakaguchi
Y
Y
Isotani
R
R
Ohmori
T
T
D001185:Artificial Intelligence; D001245:Association Learning; D001921:Brain / Q000502:physiology*; D006801:Humans; D007802:Language; D008568:Memory; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology; D012371:Robotics; D013569:Synapses / Q000502:physiology