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 ------------------------------------------------------------------------------ 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 ------------------------------------------------------------------------------ 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 ------------------------------------------------------------------------------ 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 ------------------------------------------------------------------------------ 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 ------------------------------------------------------------------------------ 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 Return form to: Ms. Michelle Carbone, IEEE Computer Society, 1730 Mass. Ave. N.W., Washington DC 20036-1903 USA. Phone : 202-371-1003 Fax : 202-728-0884. Name (Last/First/MI) : Name to use on Badge : Company : Street Address/Mailstop : City/State/Zip/Country : Day Phone : Fax Phone : IEEE/CS membership # : 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): Advance (before 2/4/91) Late/On Site (after 2/4/91) [ ] Member/Student $150 [ ] Member/Student $180 [ ] Non-member $185 [ ] Non-member $225 CONFERENCE REGISTRATION: Advance (before 2/4/91) Late/On Site (after 2/4/91) [ ] Member $245 [ ] Member $290 [ ] Non-member $310 [ ] Non-member $365 [ ] Student $ 90 [ ] Student $100 TOTAL ENCLOSED: $ Note : Payment must be enclosed. Please make checks payable to IEEE Computer Society. All payment must be in U.S. Dollars, drawn on U.S. banks. 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Please be advised that the hotel check-in time is after 3 pm and the check-out time is 11am. Type of acommodation requested: [ ] Single $130 Single (plus 11% tax) [ ] Double (2 persons/1 bed) $145 Double (plus 11% tax) [ ] Double Double (2 persons/2 beds) $145 Double Double (plus 11% tax) Deposits refunded if cancellation notice is received 21 days prior to arrival. Name: Company/Group: Street Address: Phone: City/State/Zip: Arrival day and date: Departure day and date: NOTE: deposit of one night's guest room is required to confirm a reservation. Method of payment: [ ] Check [ ] American Express [ ] VISA [ ] Mastercard [ ] Diners Club [ ] Carte Blanche Cardholder name: Card number: Expiration date: Signature: -- +----------------------------------------------------------------------+ | Tim Finin finin@prc.unisys.com | | Center for Advanced Information Technology 215-648-2840, -2288(fax) | | Unisys, PO Box 517, Paoli, PA 19301 USA 215-386-1749 (home) |