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Artificial Intelligence Research at Rutgers AI Magazine Volume 3 Number 2 (1982) (© AAAI) Research in Progress AI Research at Rutgers Edited by: Tom M. Mitchell Department of Computer Science Rutgers Unaversity New Brunswick, New Jersey 08903 RESEARCH by members of the Department of Computer projects and collaborations with researchers from other in- Science at Rutgers, and by their collaborators, is organized stitutions. The Rutgers Resource is part of the national AliU within the Laboratory for Computer Science Research (LCSR). (AI in Medicine) project which has been supported by NIH AI and AI-related applications are the major area of research since 1974. within LCSR, with about forty people-faculty, staff and graduate students-currently involved in various aspects of More recently, a number of newer AI research projects AI research. have grown within LCSR. Research on AI applications to One project which has had a major impact on the Digital System Design is being conducted under DARPA stimulation and growth of AI research at Rutgers is the Re- sponsorship, with Tom Mitchell and Saul Amarel as Co- search Resource on Computers in Biomedicine, which was Principal Investigators. Research on Al approaches to the started by Saul Amarel in 1971, and has been supported by study of Legal Reasoning is supported by NSF, with Thorne NIH since that time. Casimir Kulikowski is Co-Principal McCarty and N. S. Sridharan as Co-Principal Investigators. Investigator of the Rutgers Research Resource. The em- Research on building AI consultation systems for Naval mis- phasis of research in this project has been on applications sion planning is supported by NRL, with C. V. Srinivasan of AI to problems of knowledge organization and reasoning as Principal Investigator. Research on Machine Learning of of the type encountered in medicine and in psychological re- Heuristics is supported by NSF, with Tom Mitchell as Prin- search. It has been the philosophy of the project from the cipal Investigator. Research on expert systems for oil ex- start to combine collaborative research on the construction ploration is supported by Amoco, with Casimir Kulikowski of high performance expert systems with core research on and Sholom Weiss as Co-Principal Investigators. And basic AI methodologies and with general system development ac- research on the Representation of Knowledge in Al and tivities that enhance the environment for AI research. The Database Theory is being conducted with Ray Reiter as Prin- Rutgers Resource involves a large number of research sub- cipal Investigator. Thus, current research at Rutgers covers a broad range This article is based on research project summaries provided by the fol- of AI concerns-from the development of expert systems in lowing people: Saul Amarel, Casimir Kulikowski, L Thorne McCarty, a variety of domains to the study of basic issues of repre- Tom Mitchell, Raymond Reiter, Charles Schmidt, N S Sridharan, C V Srinivasan, and Shalom Weiss Jo Ann Gabinelli provided valu- sentation and inference. In the following, we summarize each able assistance in organizing and formating the articles of the research projects mentioned above. 36 THE AI MAGAZINE Spring 1982 Expert Systems Research it possible to move incrementally and rapidly in t,he con- struction of a new medical knowledge base in collaboration Participants: Casimir Kulikowski, Sholom Weiss, Peter with expert clinical researchers. Moreover, this experience is Politakis, John Kastner, George Drastal, Chidanand leading us to the development of a methodology for guiding Apte the interaction of medical and computer science researchers Software Support: Kevin Kern, Michael Uschold in model building. The sequence of developments of consul- tation models follows a natural progression, aided at each Research Support: NH (BRP), Amoco Production Com- step by an interplay between the clarification of medical con- pany cepts and the application of logical methods of model design. Background. Research in the area of expert sys- Our work in this area is contributing to a better understand- tems has developed from our experience in building con- ing of a central problem in the application of Artificial In- sultation programs in a number of application domains telligence to the design of expert computer-based systems; (Weiss, Kulikowski, and Safir, 1978; Lindberg et al., 1980; namely, what are the representations, the processes, and the Kulikowski, Weiss, and Galen, 1981; Kulikowski, 1980). interface facilities that are needed to acquire, augment, and The EXPERT system (Weiss and Kulikowski, 1979) is a refine knowledge bases of different types by interacting with generalized scheme for building expert reasoning models, ex- specialists in a domain. ercising them with individual problems, testing and analyz- A number of improvements in the EXPERT scheme have ing their performance on large numbers of problem-types, come about from the work in this domain. Because of the and improving them by knowledge base refinement tech- need to facilitate the acquisition of reasoning rules, we de- niques. The system has been operational on DEC lo/20 com- veloped a criterion-based scheme for defining the diagnos- puters since 1978; versions also exist on VAX and IBM com- tic rules. A knowledge-acquisition front end for EXPERT puters This system has been used by specialists in medicine, prompts the model builder for the major and minor findings, biomedical modeling, oil exploration, and chemistry to build necessary and exclusionary conditions for the presence of a models that capture their expertise in problem solving. In disease at various levels of cert,ainty. 1981 we complet,ed an interesting technology transfer experi- In ophthalmology (Weiss, Kulikowski, and Safir, 1978), ment in which a model for the interpretation of serum protein research includes a neuro-ophthalmological model developed electrophoresis patterns was automatically translated from by Dr. W. Hart at Washington University, a glaucoma model its EXPERT representation into algorithmic form, and then by Dr. Y. Kitazawa at Tokyo University, and an infectious automatically translated into assembler code for running on eye disease model by Dr. Chandler Dawson at the University a microprocessor (Weiss, KuIikowski, and Galen, 1981). of California at San Francisco. The elaboration of a special- The EXPERT system is unusual among knowledge-based ized treatment strategy and explanation model has received AI systems in that efficiency is a major design goal. This strong support through the infectious eye disease project. permits rapid analysis of cases, evaluation of performance In clinical pathology, we have collaborated with Dr. over large numbers of cases, and working in real time with Robert Galen of Columbia University and Overlook Hospi- large size models. The system is also easily portable, being tal in the development of models for the interpretation of written in FORTRAN The types of consultation problems serum protein electrophoretic patterns, thyroid tests, and best suited for EXPERT are classification problems. These LDH/CPK isoenzymes (Kulikowski, Weiss, and Galen, 1981), are problems which have a predetermined list of potential which are some of the most frequently used laboratory tests conclusions which the program can combine into interpreta- Expert Systems in Oil Exploration. In this project tion or advice sequences. PROSPECTOR and EMYCIN are we are concerned with problems of expert reasoning in oil ex- also knowledge-based systems which specialize in forms of ploration, concentrating on problems of well-log interpreta- classification problems. tion. Work is proceeding in close collaboration with experts Collaborative research projects in medicine. EX- at the Amoco Research Labs in Tulsa, Oklahoma. Well log PERT is being used extensively in the development of several interpretation is of critical importance in exploration and medical consultation models in collaboration with clinical in- production in the oil industry. Once a well has been drilled, vestigators in rheumatology, ophthalmology, clinical pathol- instruments are placed downhole and readings are recorded ogy, and with researchers in biomedical modeling. providing information on the geology below. This research Problems in rheumatology are particularly important in takes advantage of existing Amoco software for graphically health care, given the high prevalence and chronic nature interpreting the logs. The application illustrates several of arthritis and related disorders. Drs. D. Lindberg and fundamental characteristics of practical expert systems, in- G. Sharp head the research team at the University of Mis- cluding the interpretation of large amounts of signal data, souri at Columbia which is developing the knowledge base in the interrelationship of mathematical models and production rheumatology using the EXPERT scheme. The experience rules in a consultation program, and the interfacing of ad- with the design of the rheumatology model (Lindberg vanced applications software to an interpretive system. In et al , 1980) has shown that the knowledge engineering tools this system, the user is guided through an interpretation (EXPERT and SEEK) and know-how developed so far make with low-keyed advice, being restrained from carrying out THE AI MAGAZINE Spring 1982 37 a particular analysis only if a necessary antecedent step has A precedence scheme for selection and explana- been omitted. However, should the intermediate results show tion of therapies. A general scheme for treatment selec- inconsistencies, or perhaps
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