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Subject: Generality in Artificial Intelligence
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From: YLIKOSKI%FINFUN.BITNET@MITVMA.MIT.EDU
Subject:  Generality in Artificial Intelligence
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This entry was inspired by John McCarthy's Turing Award lecture in
Communications of the ACM, December 1987, Generality in Artificial
Intelligence.


> "In my opinion, getting a language for expressing general
> commonsense knowledge for inclusion in a general database is the key
> problem of generality in AI."


What is commonsense knowledge?


Here follows an example where commonsense knowledge plays its part.  A
human parses the sentence

"Christine put the candle onto the wooden table, lit a match and lit
it."

The difficulty which humans overcome with commonsense knowledge but
which is hard to a program is to determine whether the last word, the
pronoun "it" refers to the candle or to the table.  After all, you can
burn a wooden table.

Probably a human would reason, within less than a second, like this.

"Assume Christine is sane.  The event might have taken place at a
party or during her rendezvous with her boyfriend.  People who do
things such as taking part in parties most often are sane.

People who are sane are more likely to burn candles than tables.

Therefore, Christine lit the candle, not the table."


It seems to me that the inferences are not so demanding but the
inferencer utilizes a large amount of background knowledge and a good
associative access mechanism.


Thus, it would seem that in order for us to see true commonsense
knowledge exhibited by a program we need:

        * a vast amount of knowledge involving the world of a person
          in virtual memory.  The knowledge involves gardening,
          Buddhism, the emotions of an ordinary person and so forth -
          its amount might equal a good encyclopaedia.
        * a good associative access mechanism.  An example of such
          an access mechanism is the hashing mechanism of the
          Metalevel Reasoning System described in/1/.


What kind of formalism should we use for expressing the commonsense
knowledge?


Modern theoretical philosophy knows of a number of logics with
different expressive power /2/.  They form a natural scale for
evaluating different knowledge representation formalisms.  For
example, it would be very interesting to know whether Sowa's
Conceptual Structures correspond to a previously known logical system.
I remember having seen a paper which complained that to a certain
extent the KRL is just another syntax for first-order predicate logic.

In my opinion, it is possible that an attempt to express commonsense
knowledge with a formalism is analogous to an attempt to fit a whale
into a tin sardine can.  The knowledge of a person has so many nuances
which are well reflected by the richness of the language used in
poetry and fiction (yes, a poem may contain nontrivial knowledge!)

Think of the Earthsea trilogy by Ursula K. LeGuin.  The climax of the
trilogy is when Sparrowhawk the wizard saves the world from Cob's evil
deeds by drawing the rune Agnen across the spring of the Dry River:

"'Be thou made whole!' he said in a clear voice, and with his staff
he drew in lines of fire across the gate of rocks a figure: the rune
Agnen, the rune of Ending, which closes roads and is drawn on coffin
lids.  And there was then no gap or void place among the boulders.
The door was shut."

Think of how difficult it would be to express that with a formalism,
preserving the emotions and the nuances.

I propose that the usage of *natural language* (augmented with
text-processing, database and NL understanding technology) for
expressing commonsense knowledge be studied.


> "Reasoning and problem-solving programs must eventually allow the
> full use of quantifiers and sets, and have strong enough control
> methods to use them without combinatorial explosion."

It would seem to me that one approach to this problem is the use of
heuristics, and a good way to learn to use heuristics well is to study
how the human brain does it.

Here follows a reference which you may now know and which will certainly
prove useful when studying the heuristic methods the human brain uses.

In 1946, the doctoral dissertation of the Dutch psychologist Adrian
D. de Groot was published.  The name of the dissertation is Het
Denken van den Schaaker, The Thinking of a Chess Player.

In the 30's, de Groot was a relatively well-known chess master.
The material of the book has been created by giving chess postitions
to Grandmasters, international masters, national masters and
first-class players and so forth for them to study.  The chess master
told aloud how he made the decision which move he thought was the best.

Good players immediately start studying the right alternatives.
Weaker players usually calculate as much but they usually follow
the wrong ideas.

Later in his life, de Groot became the education manager of the
Philips Corporation and the professor of Psychology in Amsterdam
University.  His dissertation was translated into English in the
60's in Stanford Institute as "Thought and Choice is Chess".


> "Whenever we write an axiom, a critic can say it is true only in a
> certain context.  With a little ingenuity, the critic can usually
> devise a more general context in which the precise form of the axiom
> does not hold.  Looking at human reasoning as reflected in language
> emphasizes this point."

I propose that the concept of a theory with a context be formalized.

A theory in logic has a set of true sentences (axioms) and a set of
inference rules which are used to derive theorems from axioms -
therefore, it can be described with a 2-tuple

        .

A theory with a context would be a 3-tuple

        

where "context" is a set of sentences.

Someone might create interesting theoretical philosophy or mathematical
logic research of this.


References:

/1/     Stuart Russell: The Compleat Guide to MRS, Stanford University

/2/     Antti Hautamaeki, a philosopher friend of mine, personal
        communication.