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AIList Digest Volume 5 Issue 282
AIList Digest Thursday, 10 Dec 1987 Volume 5 : Issue 282
Today's Topics:
Queries - OPS83 Execution Profiling & Expert System References &
Epistemic Logic Examples & Planning Papers &
UNISYS Master Apprentice Program,
AI Tools - Semantic Nets & Mac Lisp and Prolog,
Philosophy - Neural Nets as Science,
Law - Can You Sue an Expert System?
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Date: 7 Dec 87 19:48:52 GMT
From: "David C. Bond" <dcbond%watvlsi.waterloo.edu@RELAY.CS.NET>
Subject: OPS83 execution profiling
At the University of Waterloo, a computer architecture called CUPID has
been developed to rapidly perform the match phase of OPS5. CUPID is
a multiprocessor which executes a distributed RETE algorithm and
returns match information to the host machine.
I am investigating the changes required to allow CUPID to evaluate
OPS83 programs. The main difference between these two languages is
OPS83's use of simple procedures in the left hand sides of rules. The
processors currently used in CUPID are simple and were designed to
quickly compare fixed fields in a pair of tokens. "Left hand
procedures" can perform numerical calculations and comparisons of
arbitrary data structures. These operations require a more
sophisticated processor than those currently used in CUPID. Two
possibilities exist: make the processors more complex so they can
perform these operations, or off-load these operations to a subhost
(e.g. 680x0 processor). The latter alternative is the simpler but I
don't know what the impact on performance will be.
What I would like to find out is:
1. generally how many of these procedures are in an OPS83 program
2. what are their general execution characteristics (i.e. execution
time).
3. how many times are they called. Note: I mean how many
times they are evaluated, *NOT* how many times rules containing
procedures in their left hand sides fire.
4. how other researchers who have proposed multi-processors for
evaluating the RETE algorithm handle "left hand procedures".
Any data on these four items would be very appreciated.
Thanks in advance,
------------------------------
Date: Mon, 07 Dec 87 16:45 EST
From: WURST%UCONNVM.BITNET@WISCVM.WISC.EDU
Subject: Expert System references...
I am a graduate student in Computer Science, and I am planning
to do an independent study project next semester in Expert Systems.
My project, as it stands now, will be to build a simple expert system
for use in a microbiology lab. I plan to write the system twice,
once in LISP, and once in PROLOG, and then compare the relative
merits of each language for expert systems.
Can anyone suggest some references to get me started? This
will be my first expert system, and I am interested in literature
on how to go about building one. I would like to see information
on designing expert systems in general, how to go about getting
the information from the domain expert, and any information on
building expert systems in LISP and PROLOG in particular. Any
help you can give me would be greatly appreciated.
----------
Karl R. Wurst
Computer Science and Engineering
University of Connecticut
BITNET: WURST@UCONNVM
'Things fall apart. It's scientific' - David Byrne
------------------------------
Date: Wed, 9 Dec 87 13:58:21 PST
From: mcvax!casun.kaist.ac.kr!skhan@uunet.UU.NET (Sangki Han)
Subject: Epistemic Logic Examples
Hi! I and my collegue have designed and implemented a theorem prover
for the epistemic logic based on Konolige's deduction model.
We want to get various meaningful or famous examples to test our prover.
Especially, it would be better if the example concerns both the knowledge
and belief of multiple agents since we want to handle that kind of situations.
Thanks in advance.
Sangki Han
------------------------------
Date: Wed, 9 Dec 87 08:54:16 PST
From: marcel%meridian@ADS.ARPA (Marcel Schoppers)
Subject: two rare papers wanted
I have been looking for the following two papers for several years, and have
been unable to get copies. I can't wait any longer -- my thesis needs them.
If you have one or both of them, *please* send me a message. So as to avoid
duplicate labor I'll let you know if someone else is already helping me out.
The articles are
Warren, DHD. "Generating conditional plans and programs" Proc
AISB Summer Conference, Edinburgh (1976), 344ff.
Sacerdoti, ED "Plan generation and execution for robotics" Rhode
Island Wshop on Robotics Research (Apr 1980).
marcel@ADS.ARPA
------------------------------
Date: 8 Dec 87 14:22 -0600
From: Imants Krumins <krumins%asd.arc.cdn%ubc.csnet@RELAY.CS.NET>
Subject: UNISYS Master Apprentice Program
I have been asked to develop a proposal for development of an expert
system under the UNISYS Master Apprentice Program (MAP).
For those unfamiliar with MAP, it is basically a program in which UNISYS
provides training and expert consulting with the goal of introducing the
client corporation to expert systems through the development of a
prototype system to "solve" an appropriate practical problem faced by
the client. The trainee will presumably have gained sufficient
expertise during MAP to complete the development of the prototype to a
production system.
My backgound/knowledge in this field consists primarily of reading this
newsgroup and a very limited amount of literature as well as low level
fooling with LISP programming. I would appreciate hearing from anyone in
the group with direct or indirect experience with MAP or expert systems
technology at UNISYS in general. Is the MAP a good way to get involved
in expert systems development? Are the MAP products of any practical
use? What backgound reading would be useful as a preparation? Any info
regarding the quality of the MAP, personnel, hardware, software, etc.
would be very useful.
I will summarize to the net if there is sufficient interest.
Imants Krumins (krumins@asd.arc.cdn)
Resource Technologies Department
Alberta Research Council
PO Box 8330, Postal Station F
Edmonton, Alberta
Canada T6H 5X2
403/450-5263
------------------------------
Date: Mon, 7 Dec 87 09:03:46 EST
From: rapaport@cs.Buffalo.EDU (William J. Rapaport)
Subject: kannan's inquiry re sem nets
I couldn't contact Kannan by email (daemon problems); so here's a
reply about sem nets:
The SNePS semantic network processing system might be what you want.
See:
Shapiro, Stuart C. (1979), ``The SNePS Semantic Network Processing System,''
in N. V. Findler (ed.),
.ul
Associative Networks
(New York: Academic Press, 1979): 179-203.
and
Shapiro, Stuart C., & Rapaport, William J. (1987),
``SNePS Considered as a Fully Intensional Propositional Semantic Network,''
in G. McCalla & N. Cercone (eds.),
.ul
The Knowledge Frontier: Essays in the Representation of Knowledge
(New York: Springer-Verlag): 262-315;
earlier version preprinted as Technical Report No. 85-15
(Buffalo: SUNY Buffalo Dept. of Computer Science, 1985);
shorter version appeared in
.ul
Proc. 5th Nat'l. Conf. on Artificial Intelligence (AAAI-86; Philadelphia)
(Los Altos, CA: Morgan Kaufmann), Vol. 1, pp. 278-83.
------------------------------
Date: Mon 7 Dec 87 09:17:32-PST
From: George S. Cole <GCOLE@Sushi.Stanford.EDU>
Subject: Re: AIList V5 #280 - Robot Kits, Mac ES Tools, Scientific
Method
Re: Expert System Shells for the Mac: Tools to Build the Tool
The paucity of shells for the Macintosh is puzzling. There are three
language environments which can be used to build such a shell currently on
the market: (1) AAIS Prolog; (2) Expertelligence's ExperCommonLisp, and
(3) Allegro Common LISP from Coral Software.
AAIS Prolog is the least expensive of the three -- but contains the
least support for moving beyond the language. The price is below $200 (as
part of a class purchase, we were able to buy it for $70 a copy). Tying new
resources into the system will require some Mac-hacking.
ExperCommonLisp comes in two varieties: plain (~$200) and chocolate
(~$800). It is an extension to LISP that allows object-oriented programming,
but lacks type-casting features. The debugger works on the compiled code
rather than the interpreted code, which can be puzzling. The expensive version
is supposed to produce stand-alone applications (but I have only used the
language).
Allegro Common LISP falls into the mid-range (~$490). It is also an
extension to Common LISP that allows object-oriented programming, contains
the full type-casting power, and is a better implementation by far. However,
it demands 2 megabytes (5 for us cautious types) and does not yet have the
"stand-alone application" power, though this is promised for the future.
George S. Cole, Esq. GCole@sushi.stanford.edu
793 Nash Av.
Menlo Park, CA 94025 (415) 322-7760
------------------------------
Date: Mon, 7 Dec 87 09:08:55 EST
From: Jim Hendler <hendler@brillig.umd.edu>
Subject: Re: Neural Nets are science
I'd like to congratulate John Nagle on his sense of humor. Without
arguing about his premise I'd like to point out that by his argument
everytime I make a phone call I am doing science by comparing my results
with Alexander Graham Bells. Building something and exploring how it
works is not even close to the scientific methodology. Experimentation
requires small little things like hypotheses and analytic methods. I hope
Mr. Nagle can succeed at developing a scientific approach to neural nets,
but comparing results??? Not even close.
------------------------------
Date: 7 Dec 87 16:54:08 GMT
From: trwrb!aero!venera.isi.edu!smoliar@ucbvax.Berkeley.EDU (Stephen
Smoliar)
Subject: Re: Can you sue an expert system?
In article <1788@cup.portal.com> Barry_A_Stevens@cup.portal.com writes:
>
>Consider, and please comment on, this scenario.
>
> * * * * * * * * * * *
>
>A well-respected, well-established expert systems(ES) company constructs
>an expert financial advisory system. The firm employs the top ES
>applications specialists in the country. The system is constructed with
>help from the top domain experts in the financial services industry. It
>is exhaustively tested, including verification of rules, verification of
>reasoning, and further analyses to establish the system's overall value.
>All results are excellent, and the system is offered for sale.
>
Anyone who is willing to accept these premises at face value may be more
interested in investing in the bridge I have between Manhattan and Brooklyn
than in expert systems. The sort of "ideal" product envisaged here is
certainly beyond the grasp of current development technology and may remain
so for quite some time. The most important omission from this scenario is
the assumption that any sort of disclaimer has been attached to the product.
I have encountered a variety of advertisements for human financial consultants;
and, as a rule, there is always some disclaimer about risk present. The
idea that their would be a machine-based product which would be risk-free
borders on ludicrous. If a customer was hooked by such a claim, most likely
the only place he would be able to complain would be to the Better Business
Bureau.
>
>By now, you know the outcome. On the Friday morning before Black Monday,
>the expert system tells Joe to "sell everything he has and go into the
>stock market." ESs can usually explain their actions, and Joe asks for
>an explanation. The ES replies "because ... it's only been going UP for
>the past five years and there are NO PROBLEMS IN SIGHT."
>
Would Joe have accepted such an explanation from a human advisor? If so,
he has gotten what he deserved. (I happened to be discussing an analogous
case with my lawyer-neighbor. Our scenario involved medical systems and
malpractice, but the theme is basically the same.)
This raises another question: Assuming Joe is no dummy (and that he can
afford good human advice), why would he be intersted in an machine advisor?
I would argue that the area in which machines tend to have it over humans
is that of quantitative risk assessment. Thus, the machine is more likely
to synthesize and justify concrete quantitative predictive models than is
a human expert, whose skills are fundamentally qualitative. Thus, the best
Joe could hope for would be such a model. INTERPRETING the model would
remain his responsibility (although that interpretation may be linked to
the machines justification of the model, itself).
I would conclude that this scenario is far too simplistic for the real world.
I suggest that Mr. Stevens debug it a bit. Then we might be able to have a
more realistic debate on the matter.
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End of AIList Digest
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