Path: utzoo!utgpu!news-server.csri.toronto.edu!bonnie.concordia.ca!thunder.mcrcim.mcgill.edu!snorkelwacker.mit.edu!usc!julius.cs.uiuc.edu!rpi!crdgw1!greenba From: greenba@gambia.crd.ge.com (ben a green) Newsgroups: comp.ai.neural-nets Subject: Re: Expert systems and neural nets Message-ID: Date: 10 Jan 91 14:10:38 GMT References: <1991Jan9.184813.15560@warwick.ac.uk> Sender: news@crdgw1.crd.ge.com Organization: GE Corporate Research & Development Lines: 47 In-reply-to: tshu@cs.warwick.ac.uk's message of 9 Jan 91 18:48:13 GMT In article <1991Jan9.184813.15560@warwick.ac.uk> tshu@cs.warwick.ac.uk (Tim Shuttleworth) writes: A former student at Warwick University, Stephen Pye, developed a network which would attempt to replace the inference engine of the original system. At a simple level, this is not such a horribly complex proposition. The conclusion reached by the original expert system depended on the responses to the questions which the user gave. Hence a particular output was due to a pattern of responses to questions, and the network simply had to perform a mapping between a set of question responses to a set of conclusions. Mr Pye produced a system which did just this. The network he designed is based on our old friend the 3 layer back-propagation network. . . . The biggest problem with the system is the user interface, or rather lack of it. In the original system, the user answered a question, and based on their response was asked further, relevant questions. The neural network, however, would like all the relevant questions to be answered at the start so it can work in parallel. However, if we give the user the option to input all responses at the start, the user is not given any sense of "focusing" on the solution, and will additionally enter responses to questions which are irrelevant to the case in hand, thus possibly providing noise which will degrade system performance. With apologies to the writer, isn't this an example of using a wrench for a hammer? Surely where rules exist, we should use them. Where they don't, enter neural networks. Think of rule-based systems as lecture and neural networks as lab. One relates to theory; the other to experience. The whole history of science since 1605 is that we need both. So, let's use expert systems to apply knowledge where we have it and call on neural networks for what must be perceived directly. The expert system shell used around here lets you call an external program for data. We let it call a neural net for pattern recognition and use the result (a pattern name) in the rule-based system. I guess it's OK to let 1000 flowers bloom, but on the other hand, life is short. -- Ben A. Green, Jr. greenba@crd.ge.com Speaking only for myself, of course.