Path: utzoo!mnetor!uunet!lll-winken!lll-tis!ames!pasteur!agate!violet.berkeley.edu!ed298-ak
From: ed298-ak@violet.berkeley.edu (Edouard Lagache)
Newsgroups: comp.ai
Subject: Re: Expert Systems in the Railroad Industry (is AI needed?).
Message-ID: <9226@agate.BERKELEY.EDU>
Date: 26 Apr 88 03:15:43 GMT
References: <8816@agate.BERKELEY.EDU> <73@edai.ed.ac.uk>
Sender: usenet@agate.BERKELEY.EDU
Reply-To: lagache@violet.berkeley.edu.UUCP (Edouard Lagache)
Distribution: comp.ai
Organization: University of California, Berkeley
Lines: 39
Keywords: AI, Expert Systems, Dynamic Programming, Appropriate Technology.

In article <73@edai.ed.ac.uk> ceb@edai (Colin Bridgewater) writes:
>  Just to get my two penn'orth in, whatever happened to dynamic programming
>for scheduling, cargo-space optimisation and inventory control etc ?  This
>well-worn technique is quite adequate for the majority of purposes envisaged
>by EL. I mention this to raise a wider issue which was possibly not in the
>mind of the original sender, namely that of the desire to throw ever more
>complex solution procedures at the simplest of problems....
>
>  Why should we want to implement an expert system, when adequate techniques 
>exist already ? That is, is the application of expert system technology
>appropriate to the magnitude and complexity of the problem ? Should we be
>advocating the application of such 'high-tech' solutions to all and sundry ?
>I have no doubt that such systems could be made to work, don't get me wrong 
>on that, I just question whether the level of technology required in order to 
>do so is justified. Surely it is better to apply the simplest solutions when-
>ever possible.
>

	Dr. Bridgewater comments are not completely off the mark.  
	One reason I posted the question was to see if Expert System
	methodologies might be useful in improving the performance
	of conventional programming techniques by providing useful
	heuristics for such tasks as switching.  While, the areas
	mentions can clearly be solved by brute force methods, it is
	unlikely that human experts employ only those sorts of 
	stategies (since human cognition doesn't support large active
	data structures); thus, there may be some interesting 
	enhancements possible on conventional programming techniques
	by learning how human experts perform the tasks involved.

	At the same time it is very much in keeping with Hubert 
	Dreyfus's comments that just railroad tasks are very 
	promising areas for expert systems that will outperform
	human experts.

	Any comments?

						Edouard Lagache
						The PROLOG Forum
						lagache@violet.berkeley.edu