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∂23-May-77  0858	FTP:BOBROW at PARC-MAXC	Panel Questions 
Mail from host Maxc2 received at 23-MAY-77 0857-PDT
Date: 23 MAY 1977 0857-PDT
From: BOBROW at PARC-MAXC
Subject: Panel Questions
To:   jmc at SAIL


A PANEL ON KNOWLEDGE REPRESENTATION

Participants and hobby horses

Daniel Bobrow 		KRL
Gary Hendrix		Semantic Nets
William Martin		OWL
John McCarthy		Predicate Calculus
Roger Schank		Scripts, Plans, and Knowledge Structures
Brian Smith		Knowledge Representation Semantics
N. Sridhiran		AIMDS


Three Questions for the Panel

In order to compare and contrast different forms of knowledge
representation, I would like each of the panel members to answer the
following three questions in no more than a thousand words (about four
pages).  Since this is very little space,  there is obviously no way
of exploring these questions in any detail.  Please give references
to relevant papers. 

Here are my answers to your questions:

Q. What are the most important premises underlying your approach to
knowledge representation, the critical ideas, and major mechanisms
used in your system?

A. At present I am trying to identify the facts about the world
that must be used in solving various kinds of problems and the modes
of reasoning available to find and validate proposed solutions.
An important premise is that the epistemological problem of what
knowledge is available to a problem solver with given opportunities
to observe and compute is substantially separable from the heuristic
problem of how then to decide what to do.  In the present stage of
research there is no "system" in the sense of a program, although
I use our proof-checker to see what the reasoning looks like.
It is also a premise, so far verified by experience, that first order
logic, i.e. extended predicate calculus, is convenient for expressing
these facts about the world.  It should be emphasized that
first order logic itself does not correspond to a language, it is rather
a basic notation within which languages can be developed.  Thus if one
first order language is found inadequate for some purpose, others
with entirely different characteristics can be tried.

Q. If your representation were being used as a basis for a system which
would conduct typed English dialogs with a user about some subject,
what aspects would your knoweldge representation make easiest;
what aspects would best be handled by building additional mechanisms.

A. Predicate calculus representations of the knowledge expressed
in English is feasible, but more difficult than has been realized
in the past.  The problem has nothing to do with the syntax of natural
languages but with the dependence of the semantics on context.  The
best work so far in this direction is Richard Montague's "English as
a Formal Language" and possibly some of the work of his followers.
However, this work does not so far take into account much of what has
been accomplished in AI, and I would do many things differently.

	While I do not expect to develop a running "Advice Taker" in
the near future, I have thought a lot about it.  While first order
logic formulas in LISP notation would be used to represent some information,
most information would be compiled into more purpose-oriented internal
forms before use.  First order logic might well be used for
communicating information.

	None of this has much relation to Kowalski's proposals to use
predicate calculus as a programming language.  I agree that this can
be done, but I have not yet seen anything to convince me that it has
many advantages as a programming language.

Q. What problem illustrates what you believe your system is best at,
and is difficult for some representations?  Point out which of your
premises and/or ideas make it possible to handle your problem
cleanly.

A. Since I don't have a "system", it is difficult to respond
precisely to the question, but here are some things that I know
how to do that I think will offer difficulty to the "systems" that
I know about.

	1. "Travel agents know what flights are available between
two cities but don't know the gates from which the airplanes leave.
They have general information about the air travel system".
A system should be able to receive this fact, in some notation,
on its input and know how to find out how to get somewhere, and know
enough to ask the travel agent how to find the gate.

	2. When asked whether President Carter is standing or
sitting a this moment, a program should say it doesn't know,
and when asked to think harder, it should say that more thinking
wouldn't help, because, as far as its information goes, he could
be doing either.  This reply should not be made if the program
has direct information about his posture.

	3. When told that Mary has the same telephone as Mike,
that Pat knows Mikes telephone number, and that Pat dialed
Mike's telephone number, the program should assent to the statement
that Pat dialed Mary's telephone number, and express ignorance
about whether Pat knows Mary's telephone number.

	4. When told the missionaries and cannibals problem in
English or in first order logic, the program should
behave differently hearing it as a puzzle and when hearing it
when it believes it is sitting by the river in a jungle.
In the former case it should reject the possibility of a bridge
across the river or a lack of oars for the boat.  In the latter
case, it should find a solution tentatively rejecting them, but
should admit them as possibilities.  It needs entities like
"a lack of oars" in order to answer questions like "What's wrong
with the boat?" and "Is that all that is wrong with the boat?".

	My general approach is described in McCarthy and Hayes
"Some Philosophical Problems from the Standpoint of Artificial
Intelligence", but most of what I have just said is based on
three as yet unpublished memoranda "First Order Theories
of Individual Concepts", "Minimal Reasoning - A Way of Jumping
to Conclusions", and "Ascribing Mental Qualities to Machines".