Abstract
In this paper, a model to represent knowledge (MORSE) that abstracts the structure of an automatic system is presented. This model is able to represent several ways of human reasoning, structured knowledge, execution strategies of an automatic system and many models presented in different works, such as hierarchical fuzzy controllers, cascade correlation neural networks architecture, decision trees, multilayer perceptrons, etc. Finally, thanks to the high level of abstraction of MORSE, the automatic systems specified by means of this model, have been classified in terms of their general features. This classification could allow a designer of systems to choose the best model of an automatic system to solve a problem. ©2000 John Wiley & Sons, Inc.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
