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From: dsn%umcp-cs.csnet@csnet-relay.arpa
Newsgroups: net.ai
Subject: Re: A call for discussion
Message-ID: <497@sri-arpa.UUCP>
Date: Fri, 30-Mar-84 12:04:36 EST
Article-I.D.: sri-arpa.497
Posted: Fri Mar 30 12:04:36 1984
Date-Received: Sat, 7-Apr-84 02:38:35 EST
Lines: 30

From:  Dana S. Nau <dsn%umcp-cs.csnet@csnet-relay.arpa>

        From:  Sal Stolfo <sal@COLUMBIA-20.ARPA>

        This  note  is  a  solicitation of the AI community for cogent
        discussion ...  We hope that all facets will be addressed including:

        - Differences between the kinds of problems encountered in AI and those
        considered more conventional.   (A   simple   answer   in   terms  of
        ``ill-defined'' and ``well-defined'' problems is viewed as a copout.)
        ...

One of the biggest differences involves how well we can explain how we
solve a problem.  The problems that humans can solve can be divided roughly
into the following two classes:

1.  Problems which we can solve which we can also explain HOW to solve.
Examples include sorting a deck of cards, adding a column of numbers, and
payroll accounting.  Any time we can explain how to solve a problem, we can
write a conventional computer procedure to solve it.

2.  Problems which we can solve but cannot explain how to solve (for a
discussion of some related issues, see Polanyi's "The Tacit Dimension").
Examples include recognizing a face, making good moves in a chess game, and
diagnosing a medical case.  We can't solve such problems using conventional
programming techniques, because we don't know what algorithms to use.
Instead, we use various heuristic approaches.

The latter class of problems corresponds roughly to what I would call AI
problems.