finin@prc.unisys.com (Tim Finin) (11/28/90)
(registration forms are included at the end of this message)
ADVANCE PROGRAM
The Seventh IEEE Conference on
ARTIFICIAL INTELLIGENCE APPLICATIONS
February 24-28, 1991
Fontainbleau Hilton Resort and Spa * Miami Beach, Florida
GENERAL CHAIR: Se June Hong, IBM
PROGRAM CHAIR: Tim Finin, Unisys
TUTORIAL CHAIR: Daniel O'Leary, USC
PUBLICITY CHAIR: Jeff Pepper, Carnegie Group
LOCAL CO-CHAIRS: Alex Pelin, Florida Int. U. & Mansur Kabuka, U. of Miami
PROGRAM COMMITTEE:
Sanjaya Addanki, IBM Donald McKay, Unisys
Jan Aikins, AION Sanjay Mittal, Metaphor Computer Sys.
Chidanand Apte, IBM Fumio Mizoguchi, Tokyo Science U.
Ron Brachman, AT&T Bell Labs Ramesh Patil, USC/ISI
Vasant Dhar, NYU David Searls, Unisys
Lee Erman, Cimflex Teknowledge Howard Shrobe, Symbolics
Robert Filman, IntelliCorp Norman Sondheimer, GE
Mark Fox, CMU Duvvuru Sriram, MIT
Peter Hart, Syntelligence Chris Tong, Rutgers U.
Steven Kimbrough, U. of Pennsylvania Wolfgang Wahlster, U. des Saarlandes
William Mark, Lockheed David Waltz, Thinking Machines Corp.
Eric Mays, IBM
LOCAL ARRANGEMENTS: Questions about local arrangements should be directed to
the local arrangements co-chairs: Prof. Alex Pelin, Florida International U.
305-348-3386, fax: 305-348-3549, pelina@servax.fiu.edu or Prof. Mansur R.
Kabuka, U. of Miami, 305-284-5566, kabuka@umiami.miami.edu.
WORKSHOPS: There will be three all-day workshops running concurrently with the
regular CAIA-91 program. These workshops will be held on Monday February 25.
To attend a workshop you must be registered for the conference and have an
invitation from the organizer. For more information, please contact the
workshop leaders directly: (1) AI and Standards, Chuck Hall, Lockheed AI
Center, 415-354-5200; (2) Interfaces Between Knowledge Based Systems and
External Systems, Tim Finin, Unisys, 215-648-2840, fax: 215-648-2288,
finin@prc.unisys.com; (3) Software Methodologies for Real Time Intelligent
Systems, Captain Sheila Banks, US Air Force, 513-255-8262, fax: 513-255-8262,
bankssb@wpafb-fdl.af.mil.
OFFICIAL CARRIER: United Airlines is the official carrier for CAIA-91.
Attendees will receive 5% off the lowest available discounted fare or 45% off
the regular coach fare. The 45% discounted fare need only be ticketed 7 days
in advance. The 5% discounted fare does have some restrictions. The number to
call for information and reservations is 800-521-4041. Attendees must make
reservations under the group number 449RB and the name IEEE Computer Society.
FOR MORE INFORMATION: For more information aboout the conference in general,
contact: IEEE Computer Society, 1730 Massachusetts Ave. NW, Washington, DC
20036, 202-371-1013, fax: 202-728-0884. For information about the technical
program, contact: Tim Finin, Unisys Center for Advanced Information Tech., PO
Box 517, Paoli PA 19301, 215-648-2840, fax: 215-648-2288, finin@prc.unisys.com.
______________________________________________________________________________
CAIA-91 TECHNICAL PROGRAM, Tuesday, February 26, 1991
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8:30 - 8:45 Chairman's Welcome Address
Se June Hong, IBM
8:45 - 10:00 Co-Plenary Talk
"AI in Biology and Challenges of the Human Genome Project"
Bruce Buchanan, University of Pittsburgh
Chair: Se June Hong, IBM
10:30 - 12:00 Panel: AI in Design: User Perspective
Chair: Duvvuru Sriram, MIT
10:30 - 12:00 Paper Session: Molecular Biology Applications
Chair: David Searls, Unisys
A Platform for Applying Multiple Machine Learning Strategies to the Task of
Learning Gene Structure
G. Christian Overton and Jon A. Pastor, Unisys
Pattern-Matching Search of DNA Sequences using Logic Grammars
David B. Searls, Unisys, and Michiel O. Noorderwier, Rutgers
Applying Bayesian Classification to Protein Structure
Lawrence Hunter and David J. States, National Library of Medicine
10:30 - 12:00 Paper Session: Innovative Database Technology
Chair: Daniel O'Leary, USC
From Parsing to Database Generation: Applying Natural Language System
Paul Jacobs, GE Research and Development Center
Automatic Cluster Assignment for Documents
Jitender S. Deogun and Sanjiv K. Bhatia, University of Nebraska,
Vijay V. Raghavan, University of Southwestern Lousiana
Extracting Company names from Text
Lisa F. Rau, GE Research and Development Center
Text Classification in Fragmented Sublanguage Domains
Robert P. Frail and Roy S. Freedman, Polytechnic University
A Knowledge Based System for the Storage and Retrieval of Images
K. Seshagiri Rao and B.E. Prasad, University of Hyderabad
12:00 - 2:00 Lunch and Sun
2:00 - 3:30 Invited Talk: "Application Projects at ICOT"
K. C. Furukawa, ICOT
Chair: Sanjay Mittal, Metaphor Computer Systems
2:00 - 3:30 Paper Session: Knowledge Acquisition and Refinement
Chair: David Waltz, Thinking Machines Corp.
IREF - An Interactive Theory-Driven Knowledge Refinement Tool
Chyouhwa Chen and Herbert Gelernter, SUNY Stony Brook
Model-Based Acquisition of Inference Structure
Xuejun Tong, Bull-LPM
Specialized Knowledge Acquisition Tool Support Compared to Manual
Development - a Case Study
Henrik Eriksson, Linkoping University
ALEX: Automatic Learning in Expert Systems
Lothar Winkelbauer and Kurt Fedra, IIASA
2:00 - 3:30 Paper Session: Rule-based Systems Theory
Chair: Ho Soo Lee, IBM
TWIN: A Parallel Scheme for a Production System Featurning both Control and
Data Parallelism
Takashi Yukawa, Tsutomu Ishikawa, Hideo Kikuchi, and Kazumitsu Matsuzawa, NTT
Use of Procedural Programming Languages for Controlling Production Systems
Toru Ishida, Yutaka Sasaki, and Yoshimi Fukuhara, NTT
Set-Oriented constructs for Rule-Based Systems
Douglas N. Gordin, AT&T, Alexander J. Pasik, Columbia University
Proving Properties of Rule-Based Systems
Richard J. Waldinger and Mark E. Stickel, SRI
4:00 - 5:45 Panel: Is Qualitative Physics Practical?
Chair: Fumio Mizoguchi, Tokyo Science University
4:00 - 5:45 Paper Session: Visualization and Cooperative Systems
Chair: D. Navinchandra, CMU
Automating the Presentation of Information
Steven F. Roth and Joe Mattis, CMU
Crystal and Molecular Structure Determination Through Imagery
Janice Glasgow and Susan Fortier, Queen's University,
Frank H. Allen, University of Cambridge
InterBALANCE: Cooperative Load-Balancing System
Michiharu Kudo and Yoshio Tozawa, IBM
Identifying Artistic Styles with Local Statistical Measures
Peter Wayner, Xerox/Cornell
A Cooperative Environment for Quantum Chemistry Environments
A.S. Fabiano and S. Chin, IBM
4:00 - 5:45 Paper Session: Hybrid Knowledge Representation Languages
Chair: Jeff Pepper, Carnegie Group
Fault Diagnosis of a Sewage Plant
J. Schonwalder, M. Hofmann and H. Langendorfer, Insitut fur Betriebssysteme
und Rechnerverbund, Germany
Knowledge Representation for Model-based High-level Specification
Hiroyuki Mizutani, Yasuko Nakayama, Katsuya Sadashige
and Takayuki Matsudaira, Toshiba, Japan
KRS - A Hybrid System for Representing Knowledge in Knowledge-Based Help
Systems
Rolf Adams, University of Karlsruhe
Knowledge Representation Support for a Software Information System
Peter G. Selfridge, AT&T Bell Laboratories
Using a Description Classifier to Enhance Deductive Inference
Robert McGregor, USC
6:00 - 7:30 RECEPTION
______________________________________________________________________________
CAIA-91 TECHNICAL PROGRAM, Wednesday, February 27, 1991
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8:30 - 9:45 Co-Plenary Talk: Toward Intelligent Systems in the DoD
Major Steven Cross, DARPA
Chair: David Waltz, Thinking Machines Corp.
10:15 - 11:45 Panel: When Does Truth Maintenance Pay Off?
Chair: Vasant Dhar, NYU
10:15 - 11:45 Paper Session: Business/Management Decision Support
Chair: Chidanand Apte
STRATUS*: A Prototype Expert Advisory System for Terminal Weather Forecasting
Michel C. Desmarais and Frances de Verteuil, CRIM,
Denis Jacob, Environment Canada, Peter Zwack, University of Quebec
Rapid Prototyping Based on Common Substrate of Knowledge
Yeona Jang, MIT, Chidanand Apte, IBM
OMNI -- A Heterogeneous Distributed Advice Giver
Meyer Billmers, Digital
AirLand Battle Management Program Decision Aids for Battle Management Planning
W.E. Wedlake, Lockheed, M.A. Hirschberg, U.S. Army
An Intelligent Assistant for Financial Hedging
Michel Benaroch and Vasant Dhar, NYU
10:15 - 11:45 Paper Session: Image Understanding
Chair: Mansuer Kabuka, University of Miami
An Assumption-Based Scene Interpretation System that Solves Multiplicity of
Scene Description
Minoru Etoh and Fumio Kishino, ATR Communications
A Multi-level Pattern Matching Method for Text Image Parsing
Michael Prussak and Jonathan J. Hull, SUNY Buffalo
Multi-Sensor Image Interpretation Using Laser Radar and Thermal Images
Chen-Chau Chu and J.K. Aggarwal, University of Texas, Austin
11:45 - 2:00 Lunch and Sun
2:00 - 3:30 Panel: Multi-Media in AI: Challenges and Opportunities
Chair: Wolfgang Wahlster, Universitaet des Saarlandes
2:00 - 3:30 Paper Session: Design and Manufacturing
Chair: Sanjay Mittal, Metaphor Computer Systems
Shape Feature Abstraction in Knowledge-based Analysis of Manufactured Products
Rajit Gadh and Friedrich B. Prinz, CMU
An Integrated System for Concurrent Design Engineering
J.A. Hernandez, Coopers and Lybrand,
S.C. Luby, P.M. Hutchins, H.W. Leung, R.E. Gustavson, T.L. DeFazio,
D.E. Whitney, J.L. Nevins, A.C. Edsall,
R.W. Metzinger and K.K. Tung, Draper Laboratory
Task Dependency Modelling to Support Assembly Plant Design
Kristina E. Fayyad and Robert Kass, Center for Machine Intelligence
Behavioral Synthesis in CADET, a Case-Based Design Tool
D. Navinchandra, Katia P. Sycara and Narasimhan, CMU
2:00 - 3:30 Paper Session: Machine Learning
Chair: Alex Pelin, Florida International University
Application of Symbolic Machine Learning to the Recognition of Texture Concepts
J.W. Bala and P.W. Pachowicz, George Mason University
Lg Depth Estimation and Ripple-Fire Characterization Using Artificial Neural
Networks
John L. Perry and Douglas R. Baumgardt, ENSCO
Learning Multiple Fault Diagnosis
Yousri El Fattah and Paul O'Rorke, University of California, Irvine
Example-Guided Optimization of Recursive Domain Theories
Ronen Feldman and Devika Subramanian, Cornell
Using Heterogeneous Learning Techniques For Identification in a Real World
Problem Domain
Anthony Van der Mude, Coopers & Lybrand
4:00 - 5:30 Invited Talk: The ESPRIT program
D. E. Talbot, Commission of the European Communities
Chair: Tim Finin, Unisys
4:00 - 5:45 Paper Session: Design
Chair: Chris Tong, Rutgers University
Automobile Transmission Design as a Constraint Satisfaction Problem: First
Results
Bernard A. Nadel and Jiang Lin, Wayne State University
A Resource-Based Paradigm for the Configuring of Technical Systems from
Modular Components
M. Heinrich and E.W. Juengst, Daimler-Benz Research Institute Berlin
Applying Qualitative Reasoning Techniques for Analysis and Evaluation in
Structural Design
Gautam Biswas, Karthik Krishnamurthy and Prodyot K. Basu, Vanderbilt University
Optimizing the Design of a Knowledge-based Design System
H. Liu, W. Wen and C.D. Rowles, Telecom Research Laboratories, Austria
Combining Rules and State Space Objects in a Configuration Expert System
Rainer Konig, Univeritat Karlsruhe,
Christian Rathke, Universitat Stuttgart
4:00 - 5:45 Paper Session: Optimization and Decision Theory
Chair: Jan Aikins, AION
Combining Decision Theory and Hierarchical Planning for a Time-Dependent
Robotic Application
Piotr J. Gmytrasiewicz, Edmund H. Durfee, and David K. Wehe, University of
Michigan
Interactive Diagnosis and Repair of Decision-Theoretic Models
David A. Klein, IBM, and Edward H. Shortliffe, Stanford
MEXSES: An Expert System for Environmental Screening
Kurt Fedra and Lothar Winkelbauer, IIASA, Austria
A Constraint Logic Programming Language for Combinatorial Optimization and
Linear Programming
Pierre Lim, Michael L. Epstein, and Edward H. Freeman, U S WEST
______________________________________________________________________________
CAIA-91 TECHNICAL PROGRAM, Thursday, February 28, 1991
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8:30 - 9:45 Keynote Address: Technology and People
Eric Bloch, former director, National Science Foundation
Chair: Tim Finin, Unisys
10:15 - 11:45 Panel: The Role of Standards in Knowledge Based Systems
Chair: Ron Ohlander, USC/ISI
10:15 - 11:45 Paper Session: Scheduling and Planning
Chair: Mark Fox, CMU
Representation and Organization of Topographic Models of Physical Spaces for
Route Planning
Ashok K. Goel, Todd J. Callantine, Murali Shankar, Georgia Institute of
Technology, and B. Chandrasekaran, Ohio State
FMS Scheduling Using Goal Directed - Conceptual Aggregation
Alok R. Chaturvedi, Purdue University,
George K. Hutchinson and Derek L. Nazareth, University of Wisconsin-Milwaukee
GIDEON: A Genetic Algorithm System for Vehicle Routing with Time Windows
Sam R. Thangiah, Kendall E. Nygard and Paul L. Juell, North Dakota State
University
10:15 - 11:45 Paper Session: Constraint/Belief Networks
Chair: Vasant Dhar, NYU
A Partitioned ATMS
Bruce D'Ambrosio and James Edwards, Oregon State University
A Cyclic Pattern Resulting from a Constraint Satisfaction Search
Holger G. Ziegeler and Hermann Kaindl, Siemens
Solving N-ary Constraint Labeling Problems Using Incremental Subnetwork
Consistency
Ho Soo Lee, IBM
11:45 - 2:00 Lunch and Sun
2:00 - 3:30 Invited Talk: "Applying Commonsense" - Necessity or Oxymoron?
Doug Lenat, MCC
Chair: Eric Mays, IBM
2:00 - 3:30 Paper Session: Dynamic Planning
Chair: Sanjaya Addanki, IBM
Influence Networks: A Reactive Planning Architecture
Lou Tychonievich, Thomas C. Smith, and Robert Evans, Martin Marietta
Plan Execution in Dynamic and Unanticipated Environments
D.D. Sharma, FMC
PEX: A Reactive Procedure Based Decision Maker
J.C. Chautard and C. Honnorat, Aerospatiale
Understanding Causal Feedback Using The Strategic Planning System (SPS)
Mitchell Smith, Peter Briggs, and Edward Freeman, U S WEST
2:00 - 3:30 Paper Session: Monitoring, Management and Uncertainty
Chair: Howard E. Shrobe, Symbolics
TEXSYS: A Large Scale Demonstration of Model-Based Real-Time Control of a
Space Station Subsystem
B.J. Glass, W.K. Erickson and K.J. Swanson, NASA-Ames
Execution Monitoring and Recovery Planning with Time
David J. Musliner, Edmund H. Durfee, and Kang G. Shin, University of Michigan
OASiX: A Real-Time Knowledge-Based System for UNIX Operations and
Administration
Se Young Park, Hyun Kyu Kang, Myung Kwan Kim, Hun Gyoo Lim, Kyung Taek
Chong, and Young Hwan Lim, ETRI
LIMA: A Logistics Inventory Management Assistant
Mark Lipshutz, Robin McEntire, and Donald P. McKay, Unisys
Uncertainty Reasoning in Prolog with Layered Meta-Interpreters
L. Umit Yalcinalp and Leon Sterling, Case Western Reserve University
4:00 - 5:30 Panel: Knowledge Sharing and the Role of Common Ontology
Chair: Tom Gruber, Stanford
4:00 - 5:30 Paper Session: Transportation Planning and Scheduling
Chair: Donald McKay, Unisys
A Knowledge-Based Approach for Railway Scheduling
Kiyotoshi Komaya and Toyoo Fukuda, Mitsubishi Electric
Intelligent Rail-Air Travel Planner
Vinay Dhawan, V.S. Rajput, and R.G.S. Asthana, Centre for Railway
Information Systems
EXDAFS: An Expert System for Dynamic Allocation of Facilities at Stations
Rahul Sinha, V.S. Rajput, and R.G.S. Asthana, Centre for Railway
Information Systems
4:00 - 5:30 Paper Session: Natural Language Processing
Chair: Wolfgang Wahlster, Universitaet des Saarlandes
Advice-Giving Using REASON: An Intelligent Assistant for Interactive Computing
Donna Lamberti and John Prager, IBM Cambridge Scientific Center
Spokesman: Data-driven, Object-Oriented Natural Language Generation
Marie W. Meteer, BBN
Exploiting Text Generation Techniques in the Provision of Help
Colin Tattersall, Leeds University
______________________________________________________________________________
CAIA-91 TUTORIAL PROGRAM
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Tutorials are three and one-half hours in length. The cost per tutorial is as
follows: for advanced registration before February 4, 1991: $150 for students
and IEEE/CS members and $185 for non-members; for registration after February
4 and on site: $180 for students and members and $225 for non-members.
TUTORIAL 1: Designing Blackboard Applications
TIME: Sunday, February 24, 1991, 8:30 am - 12:00 noon
LECTURER: Daniel Corkill, UMass and Blackboard Technology Group,
and Rajendra T. Dodhiawala, FMC
The blackboard paradigm is a powerful and flexible problem-solving
architecture. The paradigm is easy to understand and the architecture is
sufficiently general to be applicable to a wide variety of applications. We
will present the significant features of blackboard systems and how they may
be used effectively. Emphasis is placed on the advantages and disadvantages of
the blackboard approach and on the characteristics of applications that make
them well-suited to blackboard technology.
We will describe the most popular blackboard architectures in use today, their
nuances, and how they are being used in applications ranging from the Pilot's
Associate to materials processing. We will also describe how to develop a
blackboard-based application. Finally, the blackboard paradigm provides a
number of problem-solving control opportunities, and we consider recent
developments in blackboard control mechanisms. The presentation will feature a
few case studies representing ongoing advanced applications.
This tutorial is suitable for knowledge engineers, software engineers,
application builders, and project managers. Familiarity with general AI
concepts is assumed. Basic knowledge of blackboard systems is helpful, but not
required.
TUTORIAL 2: User Modeling
TIME: Sunday, February 24, 1991, 8:30 am - 12:00 noon
LECTURER: Alfred Kobsa, Universitaet des Saarlandes
User models have recently attracted strong research interest. It has become
evident that a flexible user-oriented dialog behavior of computer systems can
be realized only if this system possesses a model of the user which contains
assumptions about his/her background knowledge as well as his/her goals and
plans in consulting the system. Research in the field of user models
investigates how such assumptions can be automatically created, represented and
exploited by the system in the course of an interaction with the user. This
tutorial will survey research and practical developments in the field.
The tutorial will discuss how user modeling can contributed to rendering
computer systems more cooperative. Examples will be presented which show the
dialog behavior of a number of implemented prototype systems that incorporate
user models. The tutorial will then cover contents of user models,
representation issues, user model acquisition techniques, exploitation of the
user model, user modeling shells, and social impact issues.
TUTORIAL 3: Expert Systems for Project Managers
TIME: Sunday, February 24, 1991, 8:30 am - 12:00 noon
LECTURER: Avron Barr, ALDO Ventures
This beginning-intermediate tutorial focuses on the software project manager's
role in the various stages of knowledge systems development. Participants will
get a "big picture" perspective on the choices that must be made during the
process, including information on:
- choosing the right applications of the technology
- planning, budgeting, resource allocation, & software team skill requirements
- general and special-purpose knowledge engineering tools and their vendors
- the role of knowledge acquisition & rapid prototyping in systems development
- knowledge base design as software design
- systems integration, fielding, maintenance and knowledge updating
- common misunderstandings about AI and knowledge systems
- caveats, pitfalls, hurdles and dangers
Emphasis will be placed on the points where the lifecycle of knowledge-based
software differs from traditional software
TUTORIAL 4: Model Based Diagnosis
TIME: Sunday, February 24, 1991, 8:30 am - 12:00 noon
LECTURER: Walter Hamscher, Price Waterhouse Technology Center
Model-based Diagnosis is a particular way of thinking about automated
diagnosis, and known under a variety of aliases such as "diagnosis from first
principles" and "diagnosis from knowledge of structure and behavior." The
key idea is to use a model of the correctly functioning system, or, more
precisely, to use knowledge about the correct behavior of the individual system
components to predict the behavior of the system as a whole. Then, deviations
from those predictions are used to identify system components that might be
failing and to choose diagnostic actions that are likely to discriminate
between competing diagnoses. This methodology has been explored in several
domains including medicine, electronics, and fluid mechanical systems, using a
variety of implementation technologies.
After attending this tutorial, those interested in constructing diagnosis
applications will be able to evaluate whether model-based diagnosis is
appropriate for their immediate problems and whether the current state of the
art is capable of addressing them.
TUTORIAL 5: Intelligent Pattern Recognition and Applications
TIME: Sunday, February 24, 1991, 8:30 am - 12:00 noon
LECTURER: Patrick S. P. Wang, MIT
Pattern recognition plays an important role in AI and expert systems,
and in fact, there is now much interaction between expert systems and
pattern analysis. The core of pattern recognition, including learning
techniques and inference, also plays an important and central role in
artificial intelligence. Visual perception, scene analysis, and image
understanding are also essential to robotic vision. On the other hand,
AI methods such as knowledge representation, semantic networks, and
heuristic searching algorithms can also be applied to improve the
pattern representation and matching techniques in many pattern
recognition problems - leading to "smart" pattern recognition.
This tutorial provides an overview of Pattern Recognition (PR) and AI,
and discusses the relation between PR and AI; concepts of learning and
inferencing; the four main approaches to PR; multi-dimensional models
for PR and object recognition; degrees of recognizability,
learnability, understandability and ambiguity; and knowledge
representation and semantic networks for PR. Several examples are given.
TUTORIAL 6: Constraint Based Reasoning: Theory and Applications
TIME: Sunday, February 24, 1991, 8:30 am - 12:00 noon
LECTURERS: Sanjay Mittal, Metaphor Computer Systems and
Bernard Nadel, Wayne State Univ.
Constraint reasoning techniques are central to many areas of Artificial
Intelligence such as machine vision, temporal and spatial reasoning,
configuration, design, and scheduling. This tutorial will cover how to
formulate aspects of various tasks as a constraint reasoning problem,
techniques for finding solutions to constraint problems, and heuristics for
controlling search.
Major topics covered in this tutorial include: the standard form of
the Constraint Satisfaction Problem (CSP) and algorithms for solving
such problems such as Backtracking, Backjumping, Forward Checking and
various network consistency techniques various heuristics for
controlling search; role of constraint reasoning in tasks such as
configuration, design, scheduling, temporal and spatial reasoning, and
machine vision; extensions to the standard CSP model for handling real
applications; and case studies of working expert systems such as Pride
and VT (mechanical design), Cossack (configuration), and WRIGHT
(spatial layout).
Audience: Intended for professionals developing applications in areas
mentioned above who are already familiar with the basic AI technologies. Also
useful for students and researchers.
TUTORIAL 7: Case Based Reasoning
TIME: Monday, February 25, 1991, 8:30 am - 12:00 noon
LECTURERS: Christopher Riesbeck, Northwestern & Janet Kolodner, Georgia Tech
Case-based reasoning (CBR) means solving problems by adapting known solutions
to previous problems. It is an alternative to rule-based reasoning, which
solves problems by chaining many independent rules together. CBR has a number
of attractive features for implementing practical expert systems, in the areas
of (1) knowledge acquisition (entering sample solutions is easier than
constructing the rules that would generate them), (2) speed (a two-step process
of retrieve and adapt replaces the combinatoric chaining of rules), and (3)
explanation (solutions can be justified by showing the prior cases they are
based on). CBR is also of interest in psychology and cognitive science, where
research has suggested that people understand and reason with fairly large
``chunks'' or templates of knowledge, and that experts learn from and refer to
prior cases when approaching new problems. The goal of this introductory
tutorial is to describe how CBR works, what its strengths and weaknesses are,
and where current research in the field is heading.
TUTORIAL 8: Object-Oriented Programming and Expert Systems
TIME: Monday, February 25, 1991, 8:30 am - 12:00 noon
LECTURERS: Jan Aikins and Mr. Paul Harmon
This tutorial will introduce participants to the concepts underlying
object-oriented programming and expert systems. We will briefly consider the
development of object-oriented programming concepts, their use in OOP languages
like C++ and Smalltalk, and their extension for knowledge engineering and
expert systems development.
We will review the most popular of the expert system building tools that
include OOP capabilities. We will consider various uses of OOP techniques in
the development of diagnostic, monitoring, configuration and planning and
scheduling applications. In addition, we will review two large expert systems
applications in detail in order to understand how object-oriented programming
has been used in two large, knowledge-based applications.
The objective of this tutorial is to introduce participants to the use of
object-oriented programming in the analysis, design and development of expert
system applications. Participants will learn OOP vocabulary as it is used in
expert systems, the special features of OOP required for knowledge-based
systems development, and the various expert system-building tools and
environments that offer OOP as a component.
The tutorial is aimed at a beginning audience, where participants have a basic
knowledge of expert systems, inferencing and knowledge acquisition and
representation.
TUTORIAL 9: AI in Engineering Design
TIME: Monday, February 25, 1991, 8:30 am - 12:00 noon
LECTURERS: D. Navinchandra, CMU, and Chris Tong, Rutgers University
Artificial intelligence techniques have been applied to a wide variety of
design problems. Because design is a very rich task, it has provided a forum
for the integration of AI techniques from areas such as machine learning,
search, analogy, qualitative reasoning, case-based reasoning, and expert
systems. Hence, the design task has served not only as an application area for
AI but is also as a means of developing new ideas in AI. An overview of
existing AI design aids and current research in this area is an important
starting point for evaluating this trend and for anticipating the capabilities
of the next generation of computer-aided design systems.
This tutorial will present examples of existing AI-based aids for design, and
explore current research in this area. Attendees should expect to acquire a
basic familiarity with the organization, representation of knowledge, and
search control employed in a number of AI-based design aids.
TUTORIAL 10: Verification: Techniques and Solutions
TIME: Monday, February 25, 1991, 1:30 pm - 5:00 pm
LECTURERS: Bob O'Keefe, RPI, and Daniel E. O'Leary, USC
Assuring the quality of an expert system is critical. A poor quality system
may make costly errors resulting in considerable damage to the user or owner
of the system, such as financial loss or human suffering. Hence verification
and validation, methods and techniques aimed at ensuring quality, are
fundamentally important. This tutorial reviews the issues, methods and
techniques of verifying and validating expert systems. Topics to be covered
include various approaches to defining the quality of a system,
knowledge-based verification methods, structuring the validation process,
validation techniques, and management of the verification and validation
process.
TUTORIAL 11: Artificial Intelligence Approaches to Scheduling
TIME: Monday, February 25, 1991, 1:30 pm - 5:00 pm
LECTURERS: Mark Fox, CMU and Monte Zweben, NASA Ames Research Center
Since the 1960s, the planning problem has captured the interest of many AI
researchers. Planning selects and sequences activities such that they
achieve one or more goals and satisfy a set of domain constraints. For the
most part, planning research has focused on finding a feasible chain of
actions that accomplish one or more goals. Scheduling selects among
alternative plans, and assigns resources and times for each activity so that
they obey the temporal restrictions of activities and the capacity limitations
of a set of shared resources. Therefore scheduling is an optimization task
where limited resources are allocated over time amongst both parallel and
sequential activities. Both problems have been proven to be NP-Hard. The goal
of this tutorial is to explicate the various scheduling problems encountered
in real-world scenarios and to suggest various AI-based techniques that
address these problems. The tutorial will explore a series of scheduling
problems with increasing complexity. Each problem class will be formally
specified as a constraint-based optimization problem and sources of difficulty
will be identified. We will then describe both AI and OR approaches (where
applicable). The tutorial is intended for a wide audience likely to include
AI practitioners, AI researchers, industry operations experts, and Operations
Research (OR) practitioners and researchers.
TUTORIAL 12: Integrating Knowledge-Based Systems and Hypermedia Systems in
Domain-Oriented Design Environments
TIME: Monday, February 25, 1991, 1:30 pm - 5:00 pm
LECTURER: Gerald Fischer, University of Colorado
This tutorial will focus on conceptual frameworks and prototype systems for
cooperative problem solving systems between humans and computers. The
tutorial challenges the basic assumption that the most widely publicized goal
of artificial intelligence (understanding and building autonomous,
intelligent, thinking machines) is also the most important one. The material
presented is based (1) on the empirical fact that most knowledge-based systems
are intended to assist human endeavor and are almost never intended to be
autonomous agents and (2) on the belief that AI methodologies and technologies
provide the unique opportunity to improve productivity by addressing, rather
than ignoring, human needs and potential.
The tutorial will introduce domain-oriented design environments which
integrate knowledge-based systems and hypermedia systems. The architecture of
this class of systems will be discussed, and several prototype systems (for
architectural design, for computer network design, and for computer
programming) will be described in detail.
______________________________________________________________________________
CAIA-91 TUTORIAL LECTURER BIOGRAPHIES
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Dr. Jan Aikins is a founder and currently Vice President of Technology for
AION, and expert system's tool vendor for IBM PC and mainframe tools. At AION
she is responsible for assessing technological developments in Artificial
Intelligence and related fields. She directs advanced development projects and
provides technological and competitive information to AION's marketing and
sales departments. Prior to joining AION, Dr. Aikins held research positions
at both Hewlett- Packard and IBM where she gained extensive experience in
creating expert systems for both scientific and commercial applications. Dr.
Aikins received her Ph.D. from Stanford University in Artificial Intelligence
in 1980.
Mr. Avron Barr is an internationally recognized authority on the business and
technology of artificial intelligence. He edited, with Professors Feigenbaum
and Cohen, the renowned four-volume reference work, The Handbook of Artificial
Intelligence. Since 1979, Mr. Barr's consulting firm, Aldo Ventures Inc., has
provided management consulting and training to a number of leading companies.
Currently, Mr. Barr is forming a new company, Compliance Knowledge Systems, to
publish knowledge-based software products that address regulatory compliance
issues.
Dr. Daniel D. Corkill received a Ph.D. in Computer Science from the University
of Massachusetts in 1983. He is a Senior Research Computer Scientist in the
Department of Computer and Information Science at the University of
Massachusetts. He is a founder of Blackboard Technology Group, specialists in
blackboard technology and support services. Dr. Corkill chaired the third and
fourth workshops on Blackboard Systems (IJCAI-89 and AAAI-90). He has
published extensively in the areas of distributed problem solving and
blackboard architectures.
Mr. Rajendra T. Dodhiawala received the M.S. in Systems Science from Louisiana
State University in 1984. He is the technical team leader of the Real-Time AI
Systems group at the Corporate Technology Center, FMC. Mr. Dodhiawala was
co-chair of the first two Blackboard Workshops (AAAI-87 and AAAI-88) and is
co-editor of BLACKBOARD ARCHITECTURES AND APPLICATIONS, Academic Press, 1989.
He has worked extensively in the area of real-time and blackboard systems.
Dr. Gerald Fischer is professor of computer science and a member of the
Institute of Cognitive Science at the University of Colorado at Boulder. His
research addresses a wide variety of topics in the areas of knowledge based
systems, human computer interaction and software design. It has led to the
development of new conceptual frameworks and to the design and implementation
of a number of innovative cooperative problem solving systems.
Dr. Mark Fox is Associate Professor of Computer Science and Robotics and
Director of the Center for Integrated Manufacturing Decision Systems at
Carnegie Mellon University. He received his BSc in Computer Science from the
University of Toronto in 1975 and his PhD in Computer Science from CMU in 1983.
He co-founded Carnegie Group, Inc. in 1984. Dr. Fox pioneered the application
of Artificial Intelligence to factory planning and scheduling problems, project
management, and material design. Research interests include knowledge
representation, constraint directed reasoning and applications of artificial
intelligence to engineering and manufacturing problems. Dr. Fox has published
over 50 papers.
Dr. Walter Hamscher has been actively researching model-based reasoning and
diagnosis since 1982, publishing research results and survey papers, presenting
numerous talks and tutorials on model-based diagnosis, and chairing the 1990
International Workshop on Principles of Diagnosis. He received his Ph.D. from
the MIT Artificial Intelligence Laboratory in 1988, for a dissertation that
described an implemented model-based diagnosis program that used novel
techniques for representing complex digital systems.
Mr. Paul Harmon is the co-author of "Expert Systems: Artificial Intelligence In
Business". He has written other books, including his latest book, "Creating
Expert Systems" which he co-authored with Brian Sawyer. Mr. Harmon has just
completed writing the "Manual For Objectvison" (Which is being published by
Addison Wesley). He is also the editor/author of the newsletter, "Intelligent
Software Strategies". Mr. Harmon has a BA in biology from Earlham College and
has done graduate work in psychology at Columbia University.
Dr. Alfred Kobsa received master degrees in Computer Science and the Social and
Economic Sciences from the University of Linz, Austria, and his Ph.D. in
Computer Science from the Technical University of Vienna. Since 1985 he has
been a senior researcher and project coordinator of the XTRA project in the
German Collaborative Research Program on AI and Knowledge Based Systems, where
he works in the fields of user modeling, knowledge representation and expert
systems. Dr. Kobsa was the co-chair of the First International Workshop on
User Modeling (UM86) in Maria Laach, Germany, in 1986.
Dr. Janet L. Kolodner is a full professor at the Georgia Institute of
Technology. Her thesis research on CYRUS was one of the first implementations
of a memory for cases. She has directed the development of numerous case-based
reasoning projects there, in domains ranging from psychiatric diagnosis to
contract negotiation to catering. She is the author of "Retrieval and
Organizational Strategies in Conceptual Memory", co-editor of "Experience,
Memory and Reasoning", and currently writing a textbook on case-based
reasoning.
Sanjay Mittal recently joined a new expert systems group at Metaphor Computer
Systems. He was a Member of Research Staff at Xerox Palo Alto Research Center
between 1982 and 1990. He started and led expert systems research projects in
mechanical design (PRIDE) and configuration (COSSACK). He also contributed to
the design of the Loops knowledge programming language. He is co-chair of the
1991 AAAI Spring Symposium on Constraint Reasoning and taught a tutorial on
this topic at AAAI-90. He serves on the editorial boards of IEEE Expert, Expert
Systems Research and Applications, Artificial Intelligence in Engineering
Design Analysis and Manufacturing, and Knowledge-Based Systems journals.
Bernard Nadel is an assistant professor of Computer Science at Wayne State
University, Detroit. He is interested in the design and analysis of algorithms
in general, particularly those applicable to Artificial Intelligence. He
co-taught the Constraint Directed Reasoning tutorial at IJCAI-89 in Detroit,
and the Constraint Reasoning tutorial at AAAI-90 in Boston. Recently he has
been collaborating with Ford Motor Co. to apply Constraint Satisfaction
techniques in the automated design of automobile power transmissions.
Dr. D. Navinchandra received his Doctor of Science (Sc.D.) in Engineering
Systems from MIT in 1987. He received his M.S. from MIT in 1985, and B.Tech.
from the Indian Institute of Technology (Delhi) in 1982. Navin is currently a
Research Associate at the Robotics Institute, Carnegie Mellon University and
an Adjunct Faculty member of the Department of Civil Engineering at CMU.
Research interests include: knowledge representation, design theories, project
management, and the application of artificial intelligence to engineering
problems. Dr. Navinchandra is originator of the concept of Green Engineering
- the study of product design for environmental friendliness without
compromising product quality. Navin has also co-chaired the annual AAAI
workshops on Design since 1988.
Bob O'Keefe is an Associate Professor in the Department of Decision Sciences
and Engineering Systems at Rensselaer Polytechnic Institute. He has a PhD from
the University of Southampton, England. He is leading research into the
validation and evaluation of expert systems and their impact on organizations,
and is presently an advisor to the Food and Agriculture Organization of the
United Nations on expert system validation. He is a member of AAAI, TIMS, ORS,
SCS, and BCS.
Dr. Daniel E. O'Leary received his Ph.D. from Case Western Reserve and his
masters degree from the University of Michigan. He is the editor of the Expert
Systems Review and on other editorial boards. He has published papers in a
number of journals including IEEE Expert, International Journal of Man-Machine
Studies, International Journal of Expert Systems: Research and Applications,
and Expert Systems with Applications. Dan has done tutorials on verification
and validation at IJCAI and other meetings.
Dr. Christopher K. Riesbeck is an associate professor in Electrical Engineering
and Computer Science at Northwestern University, and a Faculty Fellow at the
Institute for the Learning Sciences. He co-authored/co-edited "Artificial
Intelligence Programming", "Inside Computer Understanding", "Inside Case-based
Reasoning" and "Experience, Memory and Reasoning", and led the development of
the first commercial case-based reasoning tool at Cognitive Systems, Inc.
Dr. Peter Struss is leader of the Advanced Reasoning Methods group at Siemens
Corporate Research and Development in Munich. He obtained a Diploma in
mathematics from the University of Goettingen and received a Ph.D. in computer
science from the University of Kaiserslautern for his work on qualitative
modeling. His active research areas are qualitative reasoning, non-monotonic
reasoning and model-based systems. He was co-chairman of the Fourth
International Workshop on Qualitative Physics in 1990 and is a program
committee member of the 1991 Workshop on Principles of Diagnosis.
Dr. Chris Tong is an assistant professor of Computer Science at Rutgers
University. He has published a number of papers in leading journals and
conferences. He was the chair of the Scientific/Engineering track of both the
1990 and 1991 Conferences on AI Applications. He was the co-chair of the 1986
AAAI workshop on AI and Design, based on which he is co-editing (with D.
Sriram) a book entitled Artificial Intelligence Approaches to Engineering
Design. Chris Tong earned his BS (summa cum laude) from Columbia University
(1978) and his PhD from Stanford University (1988).
Dr. Patrick S. P. Wang has been a visiting scientist at MIT Artificial
Intelligence Laboratory, 1989-1990, on leave from Northeastern University. He
received his Ph.D. degree in computer science from Oregon State University, his
M.S.I.C.S. degree from Georgia Institute of Technology, his M.S.E.E. degree
from National Taiwan University and his B.S.E.E. degree from National Chiao
Tung University. Prof. Wang had edited four books, and published over sixty
technical papers in imaging technology, pattern recognition and artificial
intelligence.
Dr. Monte Zweben is Deputy Chief, Artificial Intelligence Research Branch NASA
Ames Research Center. His research interests include Knowledge-based
scheduling and its application to Space problems.
IEEE CAIA-91 CONFERENCE REGISTRATION
February 24-28, 1991 * Fontainebleau Hilton * Miami, Florida, USA
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TUTORIALS - February 24 and 25, 1991
[ ] 1 Designing Blackboard Operations [ ] 7 Case Based Reasoning
[ ] 2 User Modelling [ ] 8 Obj-Oriented Prog. & Exp Sys
[ ] 3 Expert Systems for Project Mgrs. [ ] 9 AI in Engineering Design
[ ] 4 Model Based Diagnosis [ ] 10 Verification: Tech. & Solutions
[ ] 5 Intel. Pattern Recognition & Appl. [ ] 11 AI Approaches to Scheduling
[ ] 6 Constraint Based Reasoning : ... [ ] 12 KB Sys and Hypermedia in Design
TUTORIAL REGISTRATION (price is per tutorial):
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CONFERENCE REGISTRATION:
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+----------------------------------------------------------------------+
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