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From: honavar@SPEEDY.WISC.EDU (A Buggy AI Program)
Newsgroups: comp.ai.digest
Subject: Re: Success of AI
Message-ID: <4622@spool.wisc.edu>
Date: Mon, 9-Nov-87 11:57:20 EST
Article-I.D.: spool.4622
Posted: Mon Nov  9 11:57:20 1987
Date-Received: Sun, 15-Nov-87 07:27:18 EST
References: <8710280748.AA21340@jade.berkeley.edu> <4357@wisdom.BITNET>
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Reply-To: honavar@speedy.wisc.edu (A Buggy AI Program)
Organization: U of Wisconsin CS Dept
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In article <4357@wisdom.BITNET> eitan%H@wiscvm.arpa (Eitan Shterenbaum) writes:
>
>As to the claim "the brain does it so why shouldn't the computer" -
>It seem to me that you forget that the brain is built slightly differently
>than a Von-Neuman machine ... It's a distributed enviorment lacking boolean
>algebra. I can hardly believe that even with all the partial solutions for
>all the complicated sets of NP problems that emulating a brain brings up, one
>might be able to present a working program. If you'd able to emulate mouse's
>brain you'd become a legend in your lifetime !
>Anyway, no one can emulate a system which has no specifications.
>if the neuro-biologists would present them then you'd have something to start
>with.

	I use the term "computer" in a sense somewhat broader than a 
	Von-Neuman machine. We can, in principle, build machines that
	incorporate distributed representations, processing and control.
	It is not clear what you mean by a "distributed environment lacking
	boolean algebra." 
	The use of fine-grained distributed representations naturally results
	in behavior indicative of processes using fuzzy or probabilistic logic.
	The goal is, not necessarily to emulate the brain in all its detail:
	We can study birds to understand the principles of aerodynamics that
	explain the phenomenon of flying and then go on to build an aeroplane
	that is very different from a bird but still obeys the same laws of
	physics. As for specifications, they can be provided in different 
	forms and at different levels of detail; Part of the exercise is
	to discover such specifications - either by studying actual existing
	systems or by analyzing the functions needed at an abstract level to
	determine the basic building blocks and how they are to be put
	together. 

>
>And last - Computers aren't meta-capable machines they have constraints,
>           not every problem has an answer and not every answermakes sense,
>           NP problems are the best example.
>
	Are you implying that humans are "meta-capable" - whatever that means?


VGH