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OCR for page 142
DISCUSSION:
-
ON EX~T SYSTEMS AND ~IR USE
Alley Newell
Bruce Buchanan Gave us a broad view of en: sys~nE; and Showed a
rather large collection of aspects amass ache hole field that need to
be worried about to ma ~ the advances MESA needs. This leads to a
po let I want to make, which concerns my own concern about whether
research is really needed on some Parts of expert systems.
-
~ -— — . .
As preparation, Figure 1 shows my current favorite diagram to
explain AI. You need to understand about AI that there are two
dimensions in terms of which to taLk about the performance of systems.
The first is the amount of immediate knowledge that they haste stored
up, that they can get ammos to. m is can con Leniently be measured by
the number of rules. m e second is the amount of knowledge that they
obtain by exploring the problem. m is can conveniently be measure] by
the number of situations examined before committing to a response.
Emus, there are isobars of equal performance, with better performance
increasing up towards the northeast. You can roughly locate different
intelligent systems in this space. Expert systems are well us on the
immediate-knowle~ge scale, without much search.
The Hitech chess
program, mice has a little, Bus not very much knowledge, lies far OUt
on the search dimension.
, ,^ _ ,
The human being is substantially above the
expert systems on the knowledge dimension.
do 1ess search than humans do. ~ ~ -
Also, most expert systems
one Anode po =t of this diagram is
teat, In one current era, expert systems are an attempt to explore what
can be achieved without very much search and reasoning, but with a
modest amount of immediately available knowledge.
If you accept the characterization of expert systems in the figure,
then even without all the research that Bruce was talking about, there
exists an interesting class of programs, even though it is very limited
~ capability. ~
. . .
m e expert systems of today constitute a class of
prcqrams that appears to be very useful if you limit the tasks to the
right kinds. Bruce was helping to characterize that. We actually know
a modest amount about this type of task.
_, _
. . —
If you have the right
knowledge assembled, then you know what to do and how to do it without
very ash involved reasoning. For such barks and their exit systems,
it is not clear that the big need is to do a lot more rarer. The
big issue is to build lots of these systems for lots of these tasks.
bat is needed is more like a development effort, to find out which
tasks can successfully be done with modest amounts of mortise. The
142
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143
In 1 10
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c:
109
1o8
107
1 o6
lo,
O 105
,~ 1 0
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~ 103
1o2
1o1
10°
~ Human
~ \
EQUIPERFORMANCE ISOBARS
-
Expert\~ \ \ \
System /\ ~ \
\ \ HItech
_ ~
Early
Al systems
-
-
1 1 1 1 1 1 1 1 1, 1
10 10 10 103 104 105 106 107 108 109 101°
SEARCH KNOWLEDGE Situations/tasks
FIGURE 1 ~n~iate knowledge versus search kna~riedge trade-off
net is not to build any more e~-sys~rn shells, or to build more
~ ols. The need is to pour all of the effort into firming out, in the
plethora of space-station tasks, which are the ones that the current
level of technology really does provide interesting and useful
solutions.
Tom Mitchell talked much more specifically than did Bruce about the
fact that the space station is a physical system--that if you want to
use expert systems and AI systems, they had better interact directly
with physical devices. ~ agree absolutely that this is a major issue
and a very important one for MESA to research. In particular, bringing
control theory and symbolic reason ng together so we understand those
as a single field is important. What I Could like to emphasize is how
little we know about that. In some respects we do not even knew the
units to use to taLk about it, or how such symbolic programs ought to
interact with control systems.
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144
To bring this point home, let me note that a lot of current effort
in understanding the human motor system is H;recte] toward exploring a
kind of system which is not controlled On detail. A particular Dynamic
system that has the right properties is composed, and is sent off to do
a motor action. A good example is Hollerbach's model of handwriting,
in which the whole system is composed of simply-interacting dynamic
subsystems, which continuously draw lett~r-like curves. which are then
__~ .~ _~_-a cabs ~ c ~ _ ~ ~ ~ —Ad_
m~ul''=~=u Ace- ~1~1~ 1~ ~ a. These dynamic systems are not cast in
concrete e They are created and torn down In seconds, in order to
compose and raCCmpC66 dynamically according to s~hort-term tack
requirements. The motor units that the cognitive system interacts with
are these co=pcsed dynamic systems. We know almost nothing about such
systems. When we finally understand something about it, I suspect it
will change our notion entirely of the interface between the symbolic
system and The Dynamic system. The point is that there is a lot of
research before we even get a clear idea clear about how symbolic
systems ought to interact with mechanical and Dynamic systems.
Tom made a suggestion about emulating devices. If a device breaks,
then the emulation can be plugged in. I th m k this is an intriguing
idea and there may be a whole world of interesting research In it. You
might counterargue that, if this is possible, then everything might as
well be run in computer mode. But there is a real reason not to do
that. Making the emulation work may take a lot of computing power.
principal reason for using real physical devices and not simulating
everything is that your system runs faster if you do not simulate it.
But that does not imply that, if one device breaks, you cannot bring to
bear an overwhelming amount of computational capacity to try to
compensate for it. Thus, the system is prepared to emulate everywhere,
but only has to do it in one or two places on any occasion. Emulation
provides a backup capability. In fact, it is never likely to be as
good, but at least it will be better than having to shut down the whole
system. I think this is an interesting path of research, which could
be pursued a long way. In particular, the feature that Tom mentioned
about thinking of ways to construct systems so that they are
decor potable and emulat~hie Bight yield many interesting possible ities.
Tom also rained the issue of sharing responsibility. However, he
did not in fact tell us much about how tasks should be shared. Rather
he described a particular aspect of the issue, which suggests that the
machine caght to learn form the human, and then, quite properly, that
the human ought to learn flus the machine. I approve of both of these
activities, but they beg the whole question of sharing. They do not
elaborate ways of sharing, but both spend a fair amount of their time
simply learning to be like each other, and confusing who really has the
knowledge and who really knows how to do what. In fact, if one has
machines with this kind of capability, the entice question of what it
means to share may get transformed. It will became extremely difficult
to quantify or be precise about who knows what, who ought to do what,
and even who is doing what in the space station. There exists a k mad
of complementarily, in which the more you spread capabilities around in
the system, so that there is a lot of redundancy, the less possible
will it be to characterize the male of system components
A
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145
effectively~to say for instance what the separate contributions are to
he pr~uctivi~ of the token station. All ~ want to Observe is that
such system; are not clean, and learning and performance get confused.
HaGrever/ even though they are not clean/ they may turn out to be the
kirk of system one has to build in order to get the margins of safety
that are needed ~ space.
Finally/ I want to talk about the issue of robustness, although it
was not a major focus of either speaker. It is a fact, I believe, that
there has been essentially no work on making expert systems robust.
There is much attention/ of course/ to their giving explanations. But
fundamentally expert systems are collections of rules, which are
ultimately brittle and unforgiving. The lack of attention to
robustness arises/ ~ part, because there is a market for programs that
are not very flexible or very robust. m ey can nevertheless, be
successful. They will be increasingly su~r=~sful, especially if the
problem is turned around by saying 'I've got this hammer; where are
interesting things to hit with it?' As a result, the expert systems
field is not focused on solving the problem that I think NEST has to
get solved, which is that it cannot use expert systems in space unless
we understand how to build robust expert systems.
A research program in robust expert systems could be fielded by
NASA, and I would certainly recommend it. Given requirements on
robustness, one could explore more redundant rule sets or the provision
of greater backtracking and reasoning mechanisms. There are many
approaches to robustness and reliability that have their analog in
expert systems and could provide guidance.
However, I think something more heroic is at stake. What is really
wrong here is the whole notion of laying dawn code--or rules, which
play the role of code for existing expert systems. That is, ~~ soon
you lay down code, it becomes an echo from the past, unadapted to the
future. You have become subject to a mechanism. Code is blind
mechanism, complex perhaps, but blind. The important thing about a
blind mechanism is that it does not care. A bullet does not care who
it kills. A broken beam does not care on whom it falls. The horror
stori-= about non-rob~,ct software almost invariably reflect the fact
that code was laid down in the past, in a fantasy land of what was
going to be, and something different happened at run time, for which
the code was not adapted.
the problem, I believe, is that the unit, the Ime of code, is
wrong. A clue for what might be right comes fray the database world,
with its adoption of transaction processing. It was concluded that the
wrong Ming to do was to take a line of code to be the unit. Mat had
to be done was to package the specification of behavior in a hanienec]
form called the transaction, for which sane guarantee= could be made.
This has the right flavor of having Charmed the nab of the unit to
_ _ _
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llama: Len I ILL - Lea::j. 1~ I~ =1~: WLUl~ ~ EVIL ~~ Age Wee 1= aged
just a little mechanism. Somehow, in the area of robustness, the
smallest unit of action has got to be, if ~ can use a metaphor, a
caring piece of action. It has to be an action, which has a big enough
context, even On its smallest unit, to react in terms of the global
goals of the system, so it can care about safety and can care about the
OCR for page 146
146
consequences of what it is Moire. Samehaw we have to find out hcw to
create units that have that property. The units carrot be rules or
code and so forth, which are just ~nisms. ~ Chink NASA ought to go
aft ~chat. It would be a great r~cPar~h project. It is mar
contribution to this symposia of a realty basic research goal that has
an exceedingly small dance of succeeding, but an incense payoff if it
does.
Representative terms from entire chapter:
device breaks
