santino@ESDVAX.ARPA.UUCP (11/23/87)
I N T E R O F F I C E M E M O R A N D U M
Date: 19-Nov-1987 12:00
From: Fred Santino
Username: SANTINO
Dept: ESD/SCPM
Tel No: x5316
TO: _MAILER! ( _DDN[AILIST@SRI.COM] )
Subject: INFO REQUESTED ON SYSTEMS DEVELOPED USING AI TOOLS/SHELLS
1. We're interested in knowing of examples of "real world" expert
systems developed using commercially available expert system
tools/shells, particularly those which have applicability to our
present "CGADS" development, and any other information useful prior to
our selecting a tool. Some preliminary background on our "CGADS"
project is provided:
2. The Computer Generated Acquisition Document System (CGADS) is the USAF
Electronic Systems Division (ESD) first-generation expert system which
assists DOD program managers and engineers in creation of acquisition
documents such as "Statements of Work" which become part of Government
"Request For Proposals" (RFP's) for major DOD systems projects.
CGADS, presently running on a VAX 8600, is used operationally by the USAF
Electronic Systems Division, as well by a large number of other DOD
acquisition agencies nationwide. CGADS is also used at the Air Force
Institute of Technology to teach systems acquisition management.
CGADS, used equally by experienced and inexperienced engineers,
presents a series of yes/no questions, such as type of equipment,
logistics, safety, production, phase of development, and degree of
commercial off-the-shelf components. Based on the engineer's
choices, CGADS generates the proper "boiler-plate" text and MIL-STD
references to form a draft Statement of Work.
Since the system text and rules are updated periodically by experts
who represent several dozen technical disciplines, the resulting
document meets most requirements, and needs only minimum review. The
system also allows newly assigned engineers, having only minimum
training, to create draft acquisition documents.
Since CGADS was first developed in 1981 exclusively in Fortran 77, and
without using a database, it has become unnecessarily expensive to
keep the text updated. Also, its structure lacks the flexibility for
planned capabilities, such as producing the greatly varying system
specifications for major DOD acquisition programs.
3. We plan to use an ORACLE database to improve the text storage, and to
select a commercial expert system tool/shell to minimize development
of an inference engine, and maintenance utility. Some examples of
AI tools we may evaluate:
Knowledge Engineering Environment (KEE), Intellicorp, Menlo Park, CA
Knowledge Engineering System (KES), Software A&E, Arlington, VA
The Intelligent Machine Model (TIMM), Gen Research, Santa Barbara, CA
OPS5, Carnegie Mellon Univ, Pittsburgh, PA
Expert, Rutgers Univ, New Brunswick, NJ
S1 or M1, Teknowledge, Inc., Palo Alto, CA
Automated Reasoning Tool (ART), Inference Corp, Los Angeles, CA
4. We'd be interested in knowing the type of application, the amount of
programming that was required to "tailor" the commercial shell/tool
for the application, and the amount of maintenance required.
In addition to providing information on actual systems developed
using commercial tools, we'd appreciate hearing any lessons learned,
or recommendations both positive and negative that anyone is willing
to share, even "horror stories" about developments that never made it,
or products to avoid (if any).
5. Please answer on AILIST, or directly to SANTINO@ESDVAX.ARPA,
or call Autovon 478-5316, or Commercial 617-377-5316.
Thanks,
Fred Santino
Project Engineer
USAF Electronic Systems Division (ESD/SCP)
Hanscom AFB, MA 01731
------AI.PETRIE@MCC.COM (Charles Petrie) (11/28/87)
Robin Steele of NCR has built a commercial expert system of some note:
. It represents and reasons about real circuit designs consisting
between 10 and 20K gates
. Customers pay $4,000+ to come into NCR's shop and use the system.
Reference: "An Expert System Application in Semicuston VLSI Design",
Robin L. Steele, _Proc. 24th ACM/IEEE Design Automation Conference_,
Miami Beach, 1987.
-------