Self-evolutional neural network knowledge base
Shigeki Sugiyama · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1998
It is now possible to construct some sort of an intelligent knowledge base by using neural networks. But this is, so called, a static knowledge base which cannot evolve itself for finding optimized answers which suit an initial aim if the initial answers do not satisfy the aim; referring to (1), (2), (3), (4), (5). However, this is the system which can behave like our human beings within a limited condition. That is to say, this can behave in a good manner only if the knowledge bases which have been implemented beforehand have enough knowledge to treat a matter to be solved. But this is not the case of usual matter, because we commonly have new unknown things to overcome in order to satisfy an aim. Now we do not have any artificial knowledge or thoughts to treat them. Because this system lacks of treating mechanism of taking one data base after another autonomously. So, in order to overcome this problem, mechanism of evolving a new knowledge base by itself for treating them until a proper answer can be found has been studied.