- Email: [email protected]
Second international expert systems conference
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The Proceedings of this Seminar are available from Mrs. M. Stephens, CAM-I, Inc., Newfoundland
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House, Poote Quay, Dorset BH15 1HJ, U.K. Tel. (0202) 670717. Telex 418457 CAMI G. Price: £40.
Second International Expert Systems Conference The Second International Expert Systems Conference and Exhibition, organised by Learned Information (Europe) Ltd., took place in London, UK from 30 September-2 October 1986. The programme comprised twenty-one sessions where papers were presented and five sessions where a range of products were reviewed. The papers considered the application and methodotogy of expert systems. In addition there was an exhibition of expert systems provided by nineteen international companies. The keynote plenary session was chaired by R.L. Schelm (CIGNA Systems, Inc., U.S.A.). The panel included: D. Shpilberg (Coopers & Lybrand, U.S.A.), K. Sonenclar (New Sciences Associates, U.S.A.), R. Milne (Intelligent Applications, U.K.) and R.S. Wa// (Texas Instruments, Inc., U.S.A.). The conference was sponsored by Expert Systems, The International Journal of Knowledge Engineering. We present below a report on the lectures delivered at this conference.
Advanced Inference and Knowledge Representation Techniques
tial. control and communication structures for an expert evaluation unit called DEXTRON, were described with an emphasis on the inferential part of the system. In conclusion he pointed out how adaptable the system was to areas outside the medical environment.
Nonmonotonic Reasoning J.G. Harper (Educational Research Centre, Ireland) and P.L. Henry (Dept. of Industrial Management, Ireland) reviewed some current problems with nonmonotonic systems of inference. In their presentation " N o n m o n o t o n i c Reasoning in the Context of (1) A Database Expert, (2) Strategy Evaluation". they also discussed the general considerations of nonmonotonic systems and made suggestions as to the domain dependency of such inferences. A framework for a nonmonotonic system was outlined. Two expert systems were described. DEXTER and SEARCrl, which incorporate some of the principles referred to. A Deductive Spreadsheet
Fuzzy Relational Products L.J. Kohout (Brunel University, U.K.) described a knowledge-based system. DEXTERON, which utitises the methodology of fuzzy relational products in the evaluation of neurological patients' dexterity. In his lecture "Evaluator of Neurological Patients Dexterity Based on Relational Fuzzy Products" he described how samples of patients' handwriting were processed and individual patterns identified using a four-stage pattern extractor. This extractor together with suitable inferen-
Improved human-machine interaction will help experts in the application domain to solve their own problems using a computer. F. Giannotti, A. Bonsignori and N. Ciaramella (Sipe Optimation SpA, F. Turini, Universith di Pisa, Italy) described in their paper " A Deductive Spreadsheet Based on a Partial Logic Evaluator" an expert system shell "Logiform". They explained that the aim of the Logiform project is the integration of Logic Programming and spreadsheet technology. The former, implemented by the Prolog language is a
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powerful and flexible declarative programming paradigm, while the latter is a very popular userfriendly interface.
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one application with a qualitative and quantitative analysis of performance. Evolutionary Process Control
Japan and North America Commercial Expert Systems
By referring to experience gained in North America J. Hewett (Ovum Ltd, U.K.) examined why expert systems are receiving so much attention (investment) even though the technology is so immature. He reviewed the different approaches by users to expert systems and the applications under development. He also illustrated the different strategies adopted by suppliers to reach their customers and reviewed the relative success of the tools that they are selling for building and using expert systems. The paper was appropriately called "Commercial Expert Systems in North America". The Fifth Generation Y. Iwashita and J. Sawamoto (Institute for New Generation Computer Technology, Japan) outlined the research and development programme of expert systems and expert systems tools at ICOT. Various logic-based experimental expert systems were described. They also summarised their experiences in designing and developing a prototype version of an expert system tool in the project. Their presentation was entitled "Development of Expert Systems in the Fifth Generation Computer Systems Project".
P. Morizet-Mahoudeaux, D. Fontaine and P. Le Beux (Universit6 de Technologie de Compi6gne, France) pointed out that the case of evolutionary processes or unstable systems especially has not been studied much. In "An Expert System for Evolutionary Process Control" they presented improvements of the expert system SUPER which enables it to manage evolutionary processes. Finally they considered ongoing research in two areas. One to establish a system to simulate any continuous evolutionary process, the other to reflect the density of data still available and the history of the consultation. Dynamic Data for Decisions R. Khanna and R.L. Moore (Lisp Machine, Inc. (LMX), U.S.A.) described in detail a real-time expert system, PICON, and its operation. In their paper "Expert Systems Involving Dynamic Data for Decisions" they pointed out that the system is currently being used in many industrial automation applications. They explained how the design of the knowledge base structure and the inference engine have evolved during the initial implementations, and that the resulting design introduces several new concepts in expert system design, appropriate for real-time application.
Financial Expert Systems I Expert Systems for Process Control
America's Financial Services Industry
Rule Based Expert Systems
In "Expert Systems in the United States of America's Financial Services Industry" R.L. Schelm (CIGNA Systems, U.S.A.) first explained the mission of his organisation Applied Research: Expert Systems (AR/ES) to explore new technologies with great potential but high risks. He went on to describe the establishment of an Expert Systems development project. Then he described other approaches being used by financial services companies to adopt the technology and listed a collection of financial services expert systems in development or production. Schelm closed his paper
In the paper "Rule Based Expert Systems - An Application in Real Time Process Control and Optimisation" J.C. Taunton (Sira Ltd, U.K.) and D.W. Haspel (Blue Circle Industries plc, U.K.) concentrated on the principles embodied in the system. The system is based on combination of traditional techniques with a special language which enables the natural expression of operational and control heuristics as a set of linguistic rules. They also presented a brief case history of
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with a consideration of unresolved problems, the most significant of which he stated was the lack of a decision-computing strategy for many financial service companies.
Medical Diagnosis System, written in Lisp, with a relational database was described.
Portfolio Management
G.M.P. O'Hare (UMIST. U.K.) discussed " N e w Directions in Distributed Artificial Intelligence". He considered the drift from centratised processing to distributed processing. He then justified the migration towards Distributed Artificial Intelligence (DAI) and outlined some notable research in the area. Emanating from this recurring problems encountered in the quest for DAI were detailed. O'Hare then focused upon the problem of heterogeneous nodes within a DAI system and proposed the need for a software system to remedy many of these. He concluded by considering the advantages of such a system and identified directions for future research.
The management of investment portfolios in the form of mutual funds, corporate asset holdings or corporate/institutional pension funds is a vital strategic planning activity. D. Kruchten (The Athena Group, U.S.A.) in "An Expert Financial Portfolio Management Advisory System" described in detail the Portfolio Management Advisor. It is a complex and comprehensive system designed to assist a professional portfolio manager in the optimal construction and maintenance of a large, long-term portfolio.
Distributed Artificial Intelligence
Corporate Tax Planning D. Shpilberg, L.E. Graham and H. Schatz (Coopers & Lybrand, U.S.A.) presented "ExperTAX: An Expert System for Corporate Tax Planning". They described how the system was designed by the accounting firm of Coopers & Lybrand. The current operating environment was described and the expert system based solution was presented. The knowledge engineering process was described in detail and novel techniques for knowledge extraction were presented. The resulting system and its knowledge base were also presented together with a discussion on detailed knowledge acquisition and ongoing knowledge based maintenance facilities.
Integrating Knowledge-Based Systems Expert and Database Systems The interaction of expert systems and databases is a topic which is receiving increasing attention. In "Expert Systems and Database Systems: How Can They Serve Each Other?" A. AI-Zobaidie and J.B. Grimson (Trinity College Dublin. Ireland) reviewed existing techniques for such interaction and described a novel dictionary-driven approach to the problem, called 'A Dictionary Interface for Expert Systems and Databases (Difcad)'. A prototype of Difead which couples a
Expert Systems Tools: Evaluations Expert System Development Packages In developing a prototype knowledge base for the control of a sinter plant four expert systems development packages were used by D.A.J. Swinkels, L. Lock Lee and M. Saunders (BHP Central Research Laboratories. Australia) to record the same knowledge. The packages were Expert-Ease, EXSYS, Insight and Xi. They were compared in terms of their ease of entering the knowledge, their speed and flexibility during the knowledge engineering phase and their speed, flexibility and ease of use by the eventual users. Insight and EXSVS were found to be the preferred packages although a combination of features from all four packages would be very useful. The paper was entitled "Comparison of Four Expert System Development Packages".
Expert System Development Tools From a random selection of expert system development tools J. van Koppen (Philips c ISA/CAD Centre, The Netherlands) provided accurate information to enable the user to make a first selection. The paper "A Survey of Expert System Development Tools" set out to place the tools and promotional materials of software vendors in their proper perspective.
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Applications Sector Overviews
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Uses of Simple Expert System Technology in Improving Training and Education".
Building Design Petrophysics By considering the nature of the building design process S. Newton (Portsmouth Polytechnic, U.K.) explored how expert systems could help. He explained in "A Role for Expert Systems in Building Design" how he had found that design decision-making could be improved by modelling the decision-making processes of various design disciplines. Each specialist can then access and compare the effects of their decisions on the decision-making of others. In this way individuals gain much broader insight into design as a total process, and a more balanced, more fully considered design solution results. Newton gave an overview of the principles underlying such an approach, and illustrated its potential by describing a developed system.
Petrophysics covers the interpretation of oil and gas well logs, recording characteristics of rock formations and their fluid (e.g. oil or gas) content as a function of depth in the wells. P. uan der Pas and L.J.B. Hoffman (Shell Laboratorium, The Netherlands) in "Knowledge Engineering Research in Petrophysics in Shell" described a research prototype of a knowledge based system called MENDEL. They suggested that it should become a flexible aid for petrophysicists and other petroleum engineers in their evaluation of oil and gas reservoirs. MENDEL'S internal structure covering both the reasoning model and the knowledge representation was discussed. In addition, a schematic example was presented.
The Nuclear Sector
Applications I In "Expert Systems in the Nuclear Sector" J.G. Kretzschmar (SCK/CEN, Belgium) pointed out the importance and complexity of the nuclear industry. He then briefly described a nuclear reactor control room operator's working environment with its potential for information overload and presented the requirements for a suitable decision support system. A systematic review of the majority of existing systems revealed different approaches with many problems still to be solved. Kretzschmar concluded that expert systems will prove useful in the nuclear sector. Training and Education N. Ford (Sheffield University, U.K.) referred to two important theories of learning, those of John Anderson and Gordon Pask. He explained how both examine the interrelationship between relatively procedural and non-procedural (declarative and descriptive) forms of knowledge and proposed a model of more, and less, effective learning based on aspects of these theories. Then he explored the extent to which simple expert system techniques may be used to facilitate more effective learning. Ford also described a prototype learning system, SPOCK (System for the Proceduralisation of Complex Knowledge). His paper was called "Novel
Archeology K.G. Baker (Research Centre for Computer Archeology, U.K.) introduced her paper "Archeology and Expert Systems: Some Problems Encountered During Practical Work" by mentioning the hesitancy some archeologists might have in adopting expert systems. She went on to review existing expert systems applied to archeology and mentioned current research. A number of reasons were given why expert systems may not be accepted as given in the general literature. Baker then went on to describe her own project, environmental archeology. She concluded optimistically that expert systems technology may be the means by which archeology will move towards being a hard science. Radar Data W. Noack, M. Pich, A. Popella, H. Runge and R. Konjack (DFVLR, FRG) dealt with the classification of an expert system as part of DFVLR'S Intelligent Synthetic Aperture Radar Processor (ISAR) which is identified by a distributed architecture using a high speed array processor, enhanced by a two-dimensional accessible memory, a front-
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end processor and a knowledge engineering workstation. They noted that in its final designation the expert system controls the entire production process including throughput and quality optimisation.
Methodology I Knowledge Engineering A methodology to be used in knowledge engineering m order to successfully design a knowledge base in an expert system was described. In "An Experience in Knowledge Engineering" A-M. Massone, M. Maury and H. Betaille (Centre de Recherche en Informatique de Montpellier) and J-C. Penochet and M. Nkgre (H6pital Colombi6re. France) also detailed the different interfaces and modules developed around the HhM~X environment. They emphasised an application in psychiatry which led to the development of an expert system called CODIAPSY.
Software and Knowledge Engineering E. Gudes, A. Shafrir and S. Gerlitz (Elron Electronic Industries, Israel) concentrated on software engineering problems in developing expert systems, and discussed techniques for overcoming them. Two basic components were stated: software development using prototyping and tools. and structured knowledge engineering which is closely tied to the prototyping technique. The usefulness of Prolog in developing prototypes and tools was also described. Their presentation was called "Software and Knowledge Engineering Methods in Building Expert Systems".
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Uncertainty in Expert Systems Uncertainty in Knowledge Engineering There are several methods of dealing with uncertainty in knowledge engineering, and debates over the validity of ways used to handle uncertainty in expert systems. "Problems of Dealing With Uncertainty in Knowledge Engineering or Knowledge Engineering is Not Black Magic" by A. Hart (Lancashire Polytechnic, u.K.) was aimed at the knowledge engineer who is tackling practical problems in industry or business and addresses three areas: the sources of and reasons for uncertainty in a knowledge domain: some problems likely to be met in handling such uncertainty; possible restrictions on expert systems in an uncertain domain. She advocated a careful selection of problems for development and warned against an undisciplined approach to project development.
Modelling of Uncertainty The lack of an adequate formalism for the modelling of uncertainty is an obstacle-to progress. In "Modelling of Uncertainty in Expert Systems" A. Gammerman and N. Creaney (Heriot-Watt University, u.K.) suggested certain minimal requirements for the representation Of such a formalism. The Prospector model, the MYCIN model and the sYsEx model were discussed in the context of these requirements and it was noted that all three have serious problems in the requirements of a logic of uncertainty. Possible areas of future research were suggested.
Rapid Prototyping
Financial Expert Systems 2
In "Control of Rapid Prototyping in Expert Systems Development" A.E.M. Oliver (Ferranti Computer Systems Ltd, u.I¢:.) described the code of practise currently in use by Ferranti Computer Systems for developing expert systems and outlined its derivation. She gave a brief historical background before considering the code of practise in detail. She concluded that the technique of rapid prototyping of expert systems should be controlled and used in conjunction with more traditional software development techniques.
A Foretgn Exchange System R. Reiter presented "FX: A Foreign Exchange Expert Advisory System". FX is a foreign exchange expert system that advises a financial professional on the most appropriate foreign currency financial instrument to use in hedging or trading. The expert system then assists in the development of an initial opening and a later follow-up option trading strategy when foreign options are the most appropriate foreign currency instrument.
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A n Expert System for a French Bank
Follow-Up Case History
J.M. Serre, A. Andersen and R. Voyer (ACT Informatique, France) described TIPI, an expert system designed to aid a bank clerk process an application for a loan. The system was designed by Arthur Andersen and is currently being tested in a number of branches in and around Paris. TIPI was developed using the expert system shell Antinea, using the implementation of Le Lisp. They concluded that TIPI was giving satisfactory results even when used by non-experts.
D. DeSalvo (American Management Systems Inc.) and J. Liebowitz (George Washington University, U.S.A.) presented "Follow-Up Case History: An Expert Information Retrieval System at the u.s. National Archives". The system engages in a dialogue with users who approach it with only vague requests for information, and helps them to clarify their request and efficiently locate the information they want. The design, development, and system assessment of this expert system prototype were described.
Information Retrieval Applications Referral The knowledge base, knowledge representation and resources, semantic processing and control mechanism of PLEXUSwere described by A. Vickery (ClS University of London), H.M. Brooks (City University) and B.C. Viekery (University College London, U.K.). PLEXUS, a working prototype of a referral tool to be used in public libraries, constitutes the first phase of the project. The second phase, also funded by the British Library, is now underway and will involve the testing, evaluation and further development of the prototype. In "Developing an Expert System for Referral" they also emphasised the constraints and difficulties encountered in the system design.
Methodology 2 Business Applications There is no established methodology for the identification of business applications suitable for expert system techniques. A practical and efficient approach can be developed from a business analysis perspective - applications can be identified at the "horizontal" and "vertical" margins of conventional data processing systems. This approach was described by R. Stow, S. Lunn and P. Slatter (Telecomputing plc, U.K.) in "How to Identify Business Applications of Expert Systems" using case studies. They emphasised that the integration of expert systems technology with conventional data processing tools and techniques is essential if businesses are to realise the full potential of expert systems.
Natural Language Interfaces Possible Expert System Implementations "Adding an Expert System Component to the Natural Language Interfaces to Relational Databases" dealt with the development of "intelligent" tools aimed at improving the retrieval facilities from large relational databases. G.P. Zarri (Centre National de la Recherche Scientifique, France) explained how when a natural query does not correspond directly to the data contained in the base, a class of inferential processes called "transformations" is applied using an inference engine. The original query is thus automatically converted into one or more semantically close ones. "Semantically close" means that the data possibly obtained with the new query will give useful information about the data originally searched for.
R.G. Moll (Ministry of Defence (Army), U.K.) in "A Method for Analysing Requirements for Possible Expert System Implementations" described a simple method consisting of three stages. It depends on an understanding of the significant characteristics of expert systems. The first stage describes the type of benefit that would result from the proposed expert system. The second stage analyses the application area using Soft Systems Methodology (after Checkland). The third stage estimates costs and benefits. The result is to allow a sensible decision to be made on whether to proceed further and build a development prototype, for which an outline specification is given.
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Business Applications for Expert Systems
Prolog Rule Acquisition
Exercising Know-How
C.D. Fares and R.Z Lucas (Savant Research Center, U.K.) presented "Prolog Rule Acquisition Via a Natural Language Interface". They described how their current expert system environ: ment consists of a Prolog interpreter tightly coupled to a commercial database and explained how it has been extremely effective in producing several prototype expert systems where a large amount of data needed to be processed: They noted a strong need for automated rule construction to obviate the need for experts to learn Prolog. The system's design was discussed and examples of rule construction were given.
A popular class of expert systems in business is informative applications. These aim to inform rather than to advise. Vital to this aim is the ability of both the expert and the end user to exercise the know-how which is used (i.e. empirical rather than casual knowledge). A number of facilities and tools now aid this process and were described by A. d'Agapeyeff and M. Barrett (Expertech Ltd, U.K.) in "Tools for Exercising Know-How".
People and Expert Systems A Man Machine Interface A survey conducted at two Haskins & Sells seminars held early in 1.986 indicated a general weariness of expert systems in U.K. businessmen and -women. Althought many thought of expert systems as relevant to their organisations, fewer than one in ten were actually using them and only one in five were even experimenting. The main reasons given for not investing were lack of resources, ignorance and concern about the maturity of the technology. In " W h y Aren't People Using Expert Systems" A.J. Morris (Deloitte Haskins & Sells, U.K.) looked at the results of the survey and tried to get behind the answers to understand people's reasons for not using expert systems.
Knowledge Acquisition Statistical Approaches In "Statistical Approaches to the Generation of Rules for Expert Systems" D. Rowley (Leicester Polytechnic, U.K.) described the development of a set o f rules for an expert system, which will enable clinicians to interrogate a database containing details of aphasic patients, H e explained that although experts in the area can assist greatly in the formulation of such rules, to succeed in framing rules with greater clarity a number of statistical techniques have to be used, particularly to deterrmne the weightings of various factors in the rules. These techniques include: discriminant analysis, cross-correlation, multiple regression, and the use of an inductive expert system, BEAGLE.
In "DIALPHIL. a Man-Machine Interface in Natural Language. Application to an Expert System" P. Trigano, P. Morizet-Mahoudeaux and P. le Beux (Universit6 de Technologie de Compirgne, France) described a system used to improve man-machine communication. This program uses both artificial intelligence and pattern matching techniques (such as dynamic comparison of words, to detect lexical errors). It builds and manages a semantic network based dictionary. All the semantic properties are deduced with a rule based system of semanuc inheritance. It also analyses a sentence, by decomposing it into different sets of words, each word being semantically normalised. DIALPHIL is now running with the expert system SUPER. and enables a user to enter data (for consultation) or rules (to build a knowledge base) written in natural language.
Applications 2 Space Allocation J-M. Andre and M. Porcheron (Laboratoires de Marcoussis. France) presented "CADOO, A Knowledge-Based System for Space Allocation", They explained how the system was applied to the layout of ship propulsion compartments. They noted that the most important aspects of CADOO are: both constraints generation and user interface provide a better environment for CADOO's designer and for a ship compartment designer. Constraints genera-
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tion uses a knowledge base of generic constraints which is easy to modify. The placement order is dynamically generated by a knowledge-based planning and meta-planning system. The search for good places is focused by constraint-dependent heuristics. The selection of the best place is done through a multi-criteria sort. Optimisation criteria are used to refine the placement. The space representation includes the use of rectangles with notches and handling areas.
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are especially important for autonomous intelligent robots where an operation is possible only on the basis of huge arrays of coded expertise, and conventional control solutions cannot be utilised because they do not operate in real time. He then discussed Autonomous Control Systems for mobile robots. Meystel went on to report that a nested hierarchical intelligent module has been developed for the knowledge-based navigation of an autonomous mobile robot. The Insight Blackboard Experiment
Highway Noise Control A number of expert systems exist that provide advice on how to set up or determine input parameters for certain simulation models. R.A. Harris and L.F. Cohn (University of Louisville, U.S.A.) presented a prototype expert system, CHINA (Computerised Highway Noise Analyst), that is capable of executing the state-of-the-art highway noise barrier design model, interpreting the output, and, if the resulting design is unacceptable, modifying the input parameters and reexecuting the model. Their paper was entitled "An Application of Expert Systems in Highway Noise Control". Diagnosis of Mechanical Failure "MULTIDIAG: A Parameterisable Expert System
for the Diagnosis of Mechanical Failure" was presented by P. Malaureille (Cap Sogeti Innovation, France). He described MULTIDIAG, its achievements, its limitations and the future developments. MULTIDIAG was built upon SITERE, which is an expert system designed to help mechanics provide diagnosis and repair automatic transmissions. SITEREis the result of a cooperation between the Renault experts and Cap Sogeti Innovation engineers.
Architecture and Techniques for Expert Systems
R.C. Muller (Systems Designers plc, U.K.) presented "The Insight Blackboard Experiment: Implications for Industry". He introduced the principles of blackboard systems and then discussed the Insight co-operative experiment and noted that Insight is now ready to invite new members and universities to participate in the project. The value to members is an opportunity to work on and evaluate the blackboard and associated techniques, with a variety of expert systems development tools. The value to universities is to provide a vehicle for projects and research into options on tools and techniques for building blackboard and opportunistic knowledge-based systems. Identifying Depositional Environment In "Identifying Depositional Environment Structure: An Expert Systems Approach Using Object-Oriented Programming and Model-Driven Verification" J. Yan and E.P. Schlumberger (France) described DENVAD. It is a second generation diagnostic type expert system. The system enables the paleo-depositional environment structure to be identified automatically which is helpful in the reconstitution of underground oil and gas reservoirs. They explained how DENVAD uses multiple and explicit knowledge representation forms via an object-oriented substrate. It has a natural and reasoning stage partition of its knowledge and takes a model-driven verification approach.
Knowledge Based Navigation
Expert Systems in Manufacturing
A. Meystel (Drexel University, U.S.A.) introduced his paper "Knowledge Based Navigation in a Descriptive State Space" by considering knowledge-based control. Knowledge-based controllers
Process Planning System In "XPLAN - An Expert Process Planning System" T. Lenau and L. Alting (Technical Univer-
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sity of Denmark, Denmark) described a system which handles the logic and decision making in manufacturing process planning. From part specifications relevant machine tools are selected and the detailed operation planning for each machine tool carried out. Facts and rules about part specifications and machine capabilities are expressed in hierarchical tree structures which make the system easy to overview. XPLAN lS used today in two industrial companies and is further linked with a commercially available CAD/CAM systems as a part of a part family and design and manufacturing module.
Lot-Sizing R.L. Vail (Trinity College Dublin. Ireland) presented "An Expert System for Lot-Sizing". He demonstrated how expert systems technology can be integrated with decision support systems to solve complex problems. The problem solved by the system is the discrete lot-sizing problem common in production planning. He explained that to construct the ordering pattern for a production item the system gathers information from various sources, applies heuristic rules, and solves complex formulas. The system integrates the capabilities of an expert system shell, a spreadsheet program and a management information system. Control of Manufacture For several years now computer programs have existed which can outperform human specialists in certain narrow fields of expertise, in terms of the conclusions the programs can draw from information they are given and request. These expert systems are the result of work in Artificial Intelligence (AI), which has the goal of creating a generally-intelligent program. In "The Control of Manufacture by Information" presented by A.W. Smith and D.R. Hughes (CIM Centre, U.K.) they attempted to look into the future to see how current and future AI products may be applied to the manufacturing process.
Knowledge Representation Representation Scheme H. Takenouchi and Y. lwashita (Institute for New Generation Computer Technology, Japan)
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outlined a knowledge representation scheme which mutually combines procedures, functions, production rules and Horn clauses. Its knowledge representation model is an imaginary organisation for performing functions of a target system, where a number of members try to solve problems systematically. They explained how the knowledge is distributed to each of the members with considerable modularity, enabling the functional specification of expert systems to be performed with less difficulty. The knowledge representation language was called (temporarily) Modular Representation Language. The paper was entitled "An Integrated Knowledge Representation Scheme for Expert Systems".
Integrated Knowledge Representation The requirement exists in Expert Database Systems for a knowledge representation scheme that can combine relational data, class hierarchies and rules into a single integrated structure. P. Russell and A. Bracher (Deductive Systems Ltd, U.K.) presented "An Integrated Knowledge Representation Scheme for Expert Database Systems". They described the knowledge representation scheme used in the Fact System. The system extends the relational model by combining it with a class membership network. This generic data is at the heart of the Fact System's power, and the new features of the system are all ultimately attributable to this.
Design Tasks Analytical and Interactive Design In "An Expert System for Analytical and Interactive Design of Control Systems" G.K.H. Pang and J-M Boyle (Cambridge University, U.K.) proposed that an expert system can work interactively with a designer, to solve analytical control engineering design problems. They considered how to structure a design problem, and how to encode design expertise as frames. They explained how these ideas are applied to the design of multi variable control systems, a non-trivial, interactive, analytical design task. They concluded by discussing how expert systems can facilitate knowledge transfer. and act as intelligent front ends to a large engineering design package.
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Expert Systems in Design A. Gairola (Digital Equipment Corporation, F.R.G.) presented "An Application of Expert Systems in Design". He described the required features of an Expert System for Design for Assembly (DFA) and partly a strategic and conceptual approach to create it. DFA is the technique to design products with ease of assembly in mind. As an example he noted that the greatest potential for minimising the complexity and cost of realising a Flexible Assembly Workstation based on robots for assembling a particular product cannot be found in robots; rather it is achieved by designing the product for easy assembly on robotised workstations. Gairola pointed out that the main objective of building an expert system is to provide designers with a tool that requires minimum effort to create such designs.
Medical Expert Systems Diagnostic and Therapeutic Aid A. Giron and P. le Beux (Universit~ de Technologie de Compi6gne, France) presented "An Expert System for Diagnostic and Therapeutic Aid for the Depressive States". They described how the system helps the non-specialist to precisely use the various classifications of the disease by asking him simple questions which are interpreted by an expert system. The system is organised in three phases: the positive diagnostic, the computerised patient profile, the anti-depressor treatment. They explained that the system is presently in the testing phase and will then be evaluated by a panel of psychiatrists and general practitioners.
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(Hospital de la S.S. "La Paz", Spain) presented "A System for Knowledge Induction and Protocol Management Aid in Oncology". They described SKIPMAO, a knowledge-based system to aid the handling and use of voluminous clinical records and to simulate the logical inference processes doctors go through in oncology therapy, both in their practice and research. Leukaemia Diagnosis P.L. Alvey (Imperial Cancer Research Fund, U.K.) and M.F. Greaves (Leukaemia Research Fund Centre, U.K.) described in "Development of a High Performance System for Leukaemia Diagnosis" a program that analyses the test results and is based entirely on the expertise of one immunologist (M. F. Greaves). They explained that the most difficult part of the task was the development of a well integrated specification for the problems of the domain, and this required many cycles of trial and error. They pointed out that the system is still being refined but already simulates the expert's opinion in the great majority of cases. Will Expert Systems Be Safe
Knowledge Induction
It is predicted that in the near future expert systems will be commonly owned by industrial, commercial and government organisations. The general public are identified as one of the possible user populations of such systems. In "Will Expert Systems Be Safe" D. Diaper (University College London, U.K.) presented an analysis of the likely development of expert systems and intelligent interfaces. The developments were discussed with a view to making such systems as safe as possible. Evidence from dialogues between users and a simulated plausible expert system with an intelligent interface were presented.
A traditional field in the application of artificial intelligence is that of "automatic diagnosis" or "diagnostic aids". Less work has been done in the area of therapeutic decision-making. A. Vi~a Cast~eiras and G. Fern~ndez FernSndez (E.T.S. Ingenieros Telecommunicacion), and J. Felih
The Proceedings of the Second International Expert Systems Conference can be ordered from Learned Information Ltd., Woodside, Hinksey Hill, Oxford 0X1 5AU, England or Learned Information, Inc., 142 Old Marlton Pike, Medford, NJ 08055, U.S.A. ISBN 0 904933 563. 586 pages.
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The Proceedings of this Seminar are available from Mrs. M. Stephens, CAM-I, Inc., Newfoundland
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House, Poote Quay, Dorset BH15 1HJ, U.K. Tel. (0202) 670717. Telex 418457 CAMI G. Price: £40.
Second International Expert Systems Conference The Second International Expert Systems Conference and Exhibition, organised by Learned Information (Europe) Ltd., took place in London, UK from 30 September-2 October 1986. The programme comprised twenty-one sessions where papers were presented and five sessions where a range of products were reviewed. The papers considered the application and methodotogy of expert systems. In addition there was an exhibition of expert systems provided by nineteen international companies. The keynote plenary session was chaired by R.L. Schelm (CIGNA Systems, Inc., U.S.A.). The panel included: D. Shpilberg (Coopers & Lybrand, U.S.A.), K. Sonenclar (New Sciences Associates, U.S.A.), R. Milne (Intelligent Applications, U.K.) and R.S. Wa// (Texas Instruments, Inc., U.S.A.). The conference was sponsored by Expert Systems, The International Journal of Knowledge Engineering. We present below a report on the lectures delivered at this conference.
Advanced Inference and Knowledge Representation Techniques
tial. control and communication structures for an expert evaluation unit called DEXTRON, were described with an emphasis on the inferential part of the system. In conclusion he pointed out how adaptable the system was to areas outside the medical environment.
Nonmonotonic Reasoning J.G. Harper (Educational Research Centre, Ireland) and P.L. Henry (Dept. of Industrial Management, Ireland) reviewed some current problems with nonmonotonic systems of inference. In their presentation " N o n m o n o t o n i c Reasoning in the Context of (1) A Database Expert, (2) Strategy Evaluation". they also discussed the general considerations of nonmonotonic systems and made suggestions as to the domain dependency of such inferences. A framework for a nonmonotonic system was outlined. Two expert systems were described. DEXTER and SEARCrl, which incorporate some of the principles referred to. A Deductive Spreadsheet
Fuzzy Relational Products L.J. Kohout (Brunel University, U.K.) described a knowledge-based system. DEXTERON, which utitises the methodology of fuzzy relational products in the evaluation of neurological patients' dexterity. In his lecture "Evaluator of Neurological Patients Dexterity Based on Relational Fuzzy Products" he described how samples of patients' handwriting were processed and individual patterns identified using a four-stage pattern extractor. This extractor together with suitable inferen-
Improved human-machine interaction will help experts in the application domain to solve their own problems using a computer. F. Giannotti, A. Bonsignori and N. Ciaramella (Sipe Optimation SpA, F. Turini, Universith di Pisa, Italy) described in their paper " A Deductive Spreadsheet Based on a Partial Logic Evaluator" an expert system shell "Logiform". They explained that the aim of the Logiform project is the integration of Logic Programming and spreadsheet technology. The former, implemented by the Prolog language is a
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powerful and flexible declarative programming paradigm, while the latter is a very popular userfriendly interface.
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one application with a qualitative and quantitative analysis of performance. Evolutionary Process Control
Japan and North America Commercial Expert Systems
By referring to experience gained in North America J. Hewett (Ovum Ltd, U.K.) examined why expert systems are receiving so much attention (investment) even though the technology is so immature. He reviewed the different approaches by users to expert systems and the applications under development. He also illustrated the different strategies adopted by suppliers to reach their customers and reviewed the relative success of the tools that they are selling for building and using expert systems. The paper was appropriately called "Commercial Expert Systems in North America". The Fifth Generation Y. Iwashita and J. Sawamoto (Institute for New Generation Computer Technology, Japan) outlined the research and development programme of expert systems and expert systems tools at ICOT. Various logic-based experimental expert systems were described. They also summarised their experiences in designing and developing a prototype version of an expert system tool in the project. Their presentation was entitled "Development of Expert Systems in the Fifth Generation Computer Systems Project".
P. Morizet-Mahoudeaux, D. Fontaine and P. Le Beux (Universit6 de Technologie de Compi6gne, France) pointed out that the case of evolutionary processes or unstable systems especially has not been studied much. In "An Expert System for Evolutionary Process Control" they presented improvements of the expert system SUPER which enables it to manage evolutionary processes. Finally they considered ongoing research in two areas. One to establish a system to simulate any continuous evolutionary process, the other to reflect the density of data still available and the history of the consultation. Dynamic Data for Decisions R. Khanna and R.L. Moore (Lisp Machine, Inc. (LMX), U.S.A.) described in detail a real-time expert system, PICON, and its operation. In their paper "Expert Systems Involving Dynamic Data for Decisions" they pointed out that the system is currently being used in many industrial automation applications. They explained how the design of the knowledge base structure and the inference engine have evolved during the initial implementations, and that the resulting design introduces several new concepts in expert system design, appropriate for real-time application.
Financial Expert Systems I Expert Systems for Process Control
America's Financial Services Industry
Rule Based Expert Systems
In "Expert Systems in the United States of America's Financial Services Industry" R.L. Schelm (CIGNA Systems, U.S.A.) first explained the mission of his organisation Applied Research: Expert Systems (AR/ES) to explore new technologies with great potential but high risks. He went on to describe the establishment of an Expert Systems development project. Then he described other approaches being used by financial services companies to adopt the technology and listed a collection of financial services expert systems in development or production. Schelm closed his paper
In the paper "Rule Based Expert Systems - An Application in Real Time Process Control and Optimisation" J.C. Taunton (Sira Ltd, U.K.) and D.W. Haspel (Blue Circle Industries plc, U.K.) concentrated on the principles embodied in the system. The system is based on combination of traditional techniques with a special language which enables the natural expression of operational and control heuristics as a set of linguistic rules. They also presented a brief case history of
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with a consideration of unresolved problems, the most significant of which he stated was the lack of a decision-computing strategy for many financial service companies.
Medical Diagnosis System, written in Lisp, with a relational database was described.
Portfolio Management
G.M.P. O'Hare (UMIST. U.K.) discussed " N e w Directions in Distributed Artificial Intelligence". He considered the drift from centratised processing to distributed processing. He then justified the migration towards Distributed Artificial Intelligence (DAI) and outlined some notable research in the area. Emanating from this recurring problems encountered in the quest for DAI were detailed. O'Hare then focused upon the problem of heterogeneous nodes within a DAI system and proposed the need for a software system to remedy many of these. He concluded by considering the advantages of such a system and identified directions for future research.
The management of investment portfolios in the form of mutual funds, corporate asset holdings or corporate/institutional pension funds is a vital strategic planning activity. D. Kruchten (The Athena Group, U.S.A.) in "An Expert Financial Portfolio Management Advisory System" described in detail the Portfolio Management Advisor. It is a complex and comprehensive system designed to assist a professional portfolio manager in the optimal construction and maintenance of a large, long-term portfolio.
Distributed Artificial Intelligence
Corporate Tax Planning D. Shpilberg, L.E. Graham and H. Schatz (Coopers & Lybrand, U.S.A.) presented "ExperTAX: An Expert System for Corporate Tax Planning". They described how the system was designed by the accounting firm of Coopers & Lybrand. The current operating environment was described and the expert system based solution was presented. The knowledge engineering process was described in detail and novel techniques for knowledge extraction were presented. The resulting system and its knowledge base were also presented together with a discussion on detailed knowledge acquisition and ongoing knowledge based maintenance facilities.
Integrating Knowledge-Based Systems Expert and Database Systems The interaction of expert systems and databases is a topic which is receiving increasing attention. In "Expert Systems and Database Systems: How Can They Serve Each Other?" A. AI-Zobaidie and J.B. Grimson (Trinity College Dublin. Ireland) reviewed existing techniques for such interaction and described a novel dictionary-driven approach to the problem, called 'A Dictionary Interface for Expert Systems and Databases (Difcad)'. A prototype of Difead which couples a
Expert Systems Tools: Evaluations Expert System Development Packages In developing a prototype knowledge base for the control of a sinter plant four expert systems development packages were used by D.A.J. Swinkels, L. Lock Lee and M. Saunders (BHP Central Research Laboratories. Australia) to record the same knowledge. The packages were Expert-Ease, EXSYS, Insight and Xi. They were compared in terms of their ease of entering the knowledge, their speed and flexibility during the knowledge engineering phase and their speed, flexibility and ease of use by the eventual users. Insight and EXSVS were found to be the preferred packages although a combination of features from all four packages would be very useful. The paper was entitled "Comparison of Four Expert System Development Packages".
Expert System Development Tools From a random selection of expert system development tools J. van Koppen (Philips c ISA/CAD Centre, The Netherlands) provided accurate information to enable the user to make a first selection. The paper "A Survey of Expert System Development Tools" set out to place the tools and promotional materials of software vendors in their proper perspective.
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Applications Sector Overviews
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Uses of Simple Expert System Technology in Improving Training and Education".
Building Design Petrophysics By considering the nature of the building design process S. Newton (Portsmouth Polytechnic, U.K.) explored how expert systems could help. He explained in "A Role for Expert Systems in Building Design" how he had found that design decision-making could be improved by modelling the decision-making processes of various design disciplines. Each specialist can then access and compare the effects of their decisions on the decision-making of others. In this way individuals gain much broader insight into design as a total process, and a more balanced, more fully considered design solution results. Newton gave an overview of the principles underlying such an approach, and illustrated its potential by describing a developed system.
Petrophysics covers the interpretation of oil and gas well logs, recording characteristics of rock formations and their fluid (e.g. oil or gas) content as a function of depth in the wells. P. uan der Pas and L.J.B. Hoffman (Shell Laboratorium, The Netherlands) in "Knowledge Engineering Research in Petrophysics in Shell" described a research prototype of a knowledge based system called MENDEL. They suggested that it should become a flexible aid for petrophysicists and other petroleum engineers in their evaluation of oil and gas reservoirs. MENDEL'S internal structure covering both the reasoning model and the knowledge representation was discussed. In addition, a schematic example was presented.
The Nuclear Sector
Applications I In "Expert Systems in the Nuclear Sector" J.G. Kretzschmar (SCK/CEN, Belgium) pointed out the importance and complexity of the nuclear industry. He then briefly described a nuclear reactor control room operator's working environment with its potential for information overload and presented the requirements for a suitable decision support system. A systematic review of the majority of existing systems revealed different approaches with many problems still to be solved. Kretzschmar concluded that expert systems will prove useful in the nuclear sector. Training and Education N. Ford (Sheffield University, U.K.) referred to two important theories of learning, those of John Anderson and Gordon Pask. He explained how both examine the interrelationship between relatively procedural and non-procedural (declarative and descriptive) forms of knowledge and proposed a model of more, and less, effective learning based on aspects of these theories. Then he explored the extent to which simple expert system techniques may be used to facilitate more effective learning. Ford also described a prototype learning system, SPOCK (System for the Proceduralisation of Complex Knowledge). His paper was called "Novel
Archeology K.G. Baker (Research Centre for Computer Archeology, U.K.) introduced her paper "Archeology and Expert Systems: Some Problems Encountered During Practical Work" by mentioning the hesitancy some archeologists might have in adopting expert systems. She went on to review existing expert systems applied to archeology and mentioned current research. A number of reasons were given why expert systems may not be accepted as given in the general literature. Baker then went on to describe her own project, environmental archeology. She concluded optimistically that expert systems technology may be the means by which archeology will move towards being a hard science. Radar Data W. Noack, M. Pich, A. Popella, H. Runge and R. Konjack (DFVLR, FRG) dealt with the classification of an expert system as part of DFVLR'S Intelligent Synthetic Aperture Radar Processor (ISAR) which is identified by a distributed architecture using a high speed array processor, enhanced by a two-dimensional accessible memory, a front-
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end processor and a knowledge engineering workstation. They noted that in its final designation the expert system controls the entire production process including throughput and quality optimisation.
Methodology I Knowledge Engineering A methodology to be used in knowledge engineering m order to successfully design a knowledge base in an expert system was described. In "An Experience in Knowledge Engineering" A-M. Massone, M. Maury and H. Betaille (Centre de Recherche en Informatique de Montpellier) and J-C. Penochet and M. Nkgre (H6pital Colombi6re. France) also detailed the different interfaces and modules developed around the HhM~X environment. They emphasised an application in psychiatry which led to the development of an expert system called CODIAPSY.
Software and Knowledge Engineering E. Gudes, A. Shafrir and S. Gerlitz (Elron Electronic Industries, Israel) concentrated on software engineering problems in developing expert systems, and discussed techniques for overcoming them. Two basic components were stated: software development using prototyping and tools. and structured knowledge engineering which is closely tied to the prototyping technique. The usefulness of Prolog in developing prototypes and tools was also described. Their presentation was called "Software and Knowledge Engineering Methods in Building Expert Systems".
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Uncertainty in Expert Systems Uncertainty in Knowledge Engineering There are several methods of dealing with uncertainty in knowledge engineering, and debates over the validity of ways used to handle uncertainty in expert systems. "Problems of Dealing With Uncertainty in Knowledge Engineering or Knowledge Engineering is Not Black Magic" by A. Hart (Lancashire Polytechnic, u.K.) was aimed at the knowledge engineer who is tackling practical problems in industry or business and addresses three areas: the sources of and reasons for uncertainty in a knowledge domain: some problems likely to be met in handling such uncertainty; possible restrictions on expert systems in an uncertain domain. She advocated a careful selection of problems for development and warned against an undisciplined approach to project development.
Modelling of Uncertainty The lack of an adequate formalism for the modelling of uncertainty is an obstacle-to progress. In "Modelling of Uncertainty in Expert Systems" A. Gammerman and N. Creaney (Heriot-Watt University, u.K.) suggested certain minimal requirements for the representation Of such a formalism. The Prospector model, the MYCIN model and the sYsEx model were discussed in the context of these requirements and it was noted that all three have serious problems in the requirements of a logic of uncertainty. Possible areas of future research were suggested.
Rapid Prototyping
Financial Expert Systems 2
In "Control of Rapid Prototyping in Expert Systems Development" A.E.M. Oliver (Ferranti Computer Systems Ltd, u.I¢:.) described the code of practise currently in use by Ferranti Computer Systems for developing expert systems and outlined its derivation. She gave a brief historical background before considering the code of practise in detail. She concluded that the technique of rapid prototyping of expert systems should be controlled and used in conjunction with more traditional software development techniques.
A Foretgn Exchange System R. Reiter presented "FX: A Foreign Exchange Expert Advisory System". FX is a foreign exchange expert system that advises a financial professional on the most appropriate foreign currency financial instrument to use in hedging or trading. The expert system then assists in the development of an initial opening and a later follow-up option trading strategy when foreign options are the most appropriate foreign currency instrument.
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A n Expert System for a French Bank
Follow-Up Case History
J.M. Serre, A. Andersen and R. Voyer (ACT Informatique, France) described TIPI, an expert system designed to aid a bank clerk process an application for a loan. The system was designed by Arthur Andersen and is currently being tested in a number of branches in and around Paris. TIPI was developed using the expert system shell Antinea, using the implementation of Le Lisp. They concluded that TIPI was giving satisfactory results even when used by non-experts.
D. DeSalvo (American Management Systems Inc.) and J. Liebowitz (George Washington University, U.S.A.) presented "Follow-Up Case History: An Expert Information Retrieval System at the u.s. National Archives". The system engages in a dialogue with users who approach it with only vague requests for information, and helps them to clarify their request and efficiently locate the information they want. The design, development, and system assessment of this expert system prototype were described.
Information Retrieval Applications Referral The knowledge base, knowledge representation and resources, semantic processing and control mechanism of PLEXUSwere described by A. Vickery (ClS University of London), H.M. Brooks (City University) and B.C. Viekery (University College London, U.K.). PLEXUS, a working prototype of a referral tool to be used in public libraries, constitutes the first phase of the project. The second phase, also funded by the British Library, is now underway and will involve the testing, evaluation and further development of the prototype. In "Developing an Expert System for Referral" they also emphasised the constraints and difficulties encountered in the system design.
Methodology 2 Business Applications There is no established methodology for the identification of business applications suitable for expert system techniques. A practical and efficient approach can be developed from a business analysis perspective - applications can be identified at the "horizontal" and "vertical" margins of conventional data processing systems. This approach was described by R. Stow, S. Lunn and P. Slatter (Telecomputing plc, U.K.) in "How to Identify Business Applications of Expert Systems" using case studies. They emphasised that the integration of expert systems technology with conventional data processing tools and techniques is essential if businesses are to realise the full potential of expert systems.
Natural Language Interfaces Possible Expert System Implementations "Adding an Expert System Component to the Natural Language Interfaces to Relational Databases" dealt with the development of "intelligent" tools aimed at improving the retrieval facilities from large relational databases. G.P. Zarri (Centre National de la Recherche Scientifique, France) explained how when a natural query does not correspond directly to the data contained in the base, a class of inferential processes called "transformations" is applied using an inference engine. The original query is thus automatically converted into one or more semantically close ones. "Semantically close" means that the data possibly obtained with the new query will give useful information about the data originally searched for.
R.G. Moll (Ministry of Defence (Army), U.K.) in "A Method for Analysing Requirements for Possible Expert System Implementations" described a simple method consisting of three stages. It depends on an understanding of the significant characteristics of expert systems. The first stage describes the type of benefit that would result from the proposed expert system. The second stage analyses the application area using Soft Systems Methodology (after Checkland). The third stage estimates costs and benefits. The result is to allow a sensible decision to be made on whether to proceed further and build a development prototype, for which an outline specification is given.
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Business Applications for Expert Systems
Prolog Rule Acquisition
Exercising Know-How
C.D. Fares and R.Z Lucas (Savant Research Center, U.K.) presented "Prolog Rule Acquisition Via a Natural Language Interface". They described how their current expert system environ: ment consists of a Prolog interpreter tightly coupled to a commercial database and explained how it has been extremely effective in producing several prototype expert systems where a large amount of data needed to be processed: They noted a strong need for automated rule construction to obviate the need for experts to learn Prolog. The system's design was discussed and examples of rule construction were given.
A popular class of expert systems in business is informative applications. These aim to inform rather than to advise. Vital to this aim is the ability of both the expert and the end user to exercise the know-how which is used (i.e. empirical rather than casual knowledge). A number of facilities and tools now aid this process and were described by A. d'Agapeyeff and M. Barrett (Expertech Ltd, U.K.) in "Tools for Exercising Know-How".
People and Expert Systems A Man Machine Interface A survey conducted at two Haskins & Sells seminars held early in 1.986 indicated a general weariness of expert systems in U.K. businessmen and -women. Althought many thought of expert systems as relevant to their organisations, fewer than one in ten were actually using them and only one in five were even experimenting. The main reasons given for not investing were lack of resources, ignorance and concern about the maturity of the technology. In " W h y Aren't People Using Expert Systems" A.J. Morris (Deloitte Haskins & Sells, U.K.) looked at the results of the survey and tried to get behind the answers to understand people's reasons for not using expert systems.
Knowledge Acquisition Statistical Approaches In "Statistical Approaches to the Generation of Rules for Expert Systems" D. Rowley (Leicester Polytechnic, U.K.) described the development of a set o f rules for an expert system, which will enable clinicians to interrogate a database containing details of aphasic patients, H e explained that although experts in the area can assist greatly in the formulation of such rules, to succeed in framing rules with greater clarity a number of statistical techniques have to be used, particularly to deterrmne the weightings of various factors in the rules. These techniques include: discriminant analysis, cross-correlation, multiple regression, and the use of an inductive expert system, BEAGLE.
In "DIALPHIL. a Man-Machine Interface in Natural Language. Application to an Expert System" P. Trigano, P. Morizet-Mahoudeaux and P. le Beux (Universit6 de Technologie de Compirgne, France) described a system used to improve man-machine communication. This program uses both artificial intelligence and pattern matching techniques (such as dynamic comparison of words, to detect lexical errors). It builds and manages a semantic network based dictionary. All the semantic properties are deduced with a rule based system of semanuc inheritance. It also analyses a sentence, by decomposing it into different sets of words, each word being semantically normalised. DIALPHIL is now running with the expert system SUPER. and enables a user to enter data (for consultation) or rules (to build a knowledge base) written in natural language.
Applications 2 Space Allocation J-M. Andre and M. Porcheron (Laboratoires de Marcoussis. France) presented "CADOO, A Knowledge-Based System for Space Allocation", They explained how the system was applied to the layout of ship propulsion compartments. They noted that the most important aspects of CADOO are: both constraints generation and user interface provide a better environment for CADOO's designer and for a ship compartment designer. Constraints genera-
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tion uses a knowledge base of generic constraints which is easy to modify. The placement order is dynamically generated by a knowledge-based planning and meta-planning system. The search for good places is focused by constraint-dependent heuristics. The selection of the best place is done through a multi-criteria sort. Optimisation criteria are used to refine the placement. The space representation includes the use of rectangles with notches and handling areas.
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are especially important for autonomous intelligent robots where an operation is possible only on the basis of huge arrays of coded expertise, and conventional control solutions cannot be utilised because they do not operate in real time. He then discussed Autonomous Control Systems for mobile robots. Meystel went on to report that a nested hierarchical intelligent module has been developed for the knowledge-based navigation of an autonomous mobile robot. The Insight Blackboard Experiment
Highway Noise Control A number of expert systems exist that provide advice on how to set up or determine input parameters for certain simulation models. R.A. Harris and L.F. Cohn (University of Louisville, U.S.A.) presented a prototype expert system, CHINA (Computerised Highway Noise Analyst), that is capable of executing the state-of-the-art highway noise barrier design model, interpreting the output, and, if the resulting design is unacceptable, modifying the input parameters and reexecuting the model. Their paper was entitled "An Application of Expert Systems in Highway Noise Control". Diagnosis of Mechanical Failure "MULTIDIAG: A Parameterisable Expert System
for the Diagnosis of Mechanical Failure" was presented by P. Malaureille (Cap Sogeti Innovation, France). He described MULTIDIAG, its achievements, its limitations and the future developments. MULTIDIAG was built upon SITERE, which is an expert system designed to help mechanics provide diagnosis and repair automatic transmissions. SITEREis the result of a cooperation between the Renault experts and Cap Sogeti Innovation engineers.
Architecture and Techniques for Expert Systems
R.C. Muller (Systems Designers plc, U.K.) presented "The Insight Blackboard Experiment: Implications for Industry". He introduced the principles of blackboard systems and then discussed the Insight co-operative experiment and noted that Insight is now ready to invite new members and universities to participate in the project. The value to members is an opportunity to work on and evaluate the blackboard and associated techniques, with a variety of expert systems development tools. The value to universities is to provide a vehicle for projects and research into options on tools and techniques for building blackboard and opportunistic knowledge-based systems. Identifying Depositional Environment In "Identifying Depositional Environment Structure: An Expert Systems Approach Using Object-Oriented Programming and Model-Driven Verification" J. Yan and E.P. Schlumberger (France) described DENVAD. It is a second generation diagnostic type expert system. The system enables the paleo-depositional environment structure to be identified automatically which is helpful in the reconstitution of underground oil and gas reservoirs. They explained how DENVAD uses multiple and explicit knowledge representation forms via an object-oriented substrate. It has a natural and reasoning stage partition of its knowledge and takes a model-driven verification approach.
Knowledge Based Navigation
Expert Systems in Manufacturing
A. Meystel (Drexel University, U.S.A.) introduced his paper "Knowledge Based Navigation in a Descriptive State Space" by considering knowledge-based control. Knowledge-based controllers
Process Planning System In "XPLAN - An Expert Process Planning System" T. Lenau and L. Alting (Technical Univer-
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sity of Denmark, Denmark) described a system which handles the logic and decision making in manufacturing process planning. From part specifications relevant machine tools are selected and the detailed operation planning for each machine tool carried out. Facts and rules about part specifications and machine capabilities are expressed in hierarchical tree structures which make the system easy to overview. XPLAN lS used today in two industrial companies and is further linked with a commercially available CAD/CAM systems as a part of a part family and design and manufacturing module.
Lot-Sizing R.L. Vail (Trinity College Dublin. Ireland) presented "An Expert System for Lot-Sizing". He demonstrated how expert systems technology can be integrated with decision support systems to solve complex problems. The problem solved by the system is the discrete lot-sizing problem common in production planning. He explained that to construct the ordering pattern for a production item the system gathers information from various sources, applies heuristic rules, and solves complex formulas. The system integrates the capabilities of an expert system shell, a spreadsheet program and a management information system. Control of Manufacture For several years now computer programs have existed which can outperform human specialists in certain narrow fields of expertise, in terms of the conclusions the programs can draw from information they are given and request. These expert systems are the result of work in Artificial Intelligence (AI), which has the goal of creating a generally-intelligent program. In "The Control of Manufacture by Information" presented by A.W. Smith and D.R. Hughes (CIM Centre, U.K.) they attempted to look into the future to see how current and future AI products may be applied to the manufacturing process.
Knowledge Representation Representation Scheme H. Takenouchi and Y. lwashita (Institute for New Generation Computer Technology, Japan)
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outlined a knowledge representation scheme which mutually combines procedures, functions, production rules and Horn clauses. Its knowledge representation model is an imaginary organisation for performing functions of a target system, where a number of members try to solve problems systematically. They explained how the knowledge is distributed to each of the members with considerable modularity, enabling the functional specification of expert systems to be performed with less difficulty. The knowledge representation language was called (temporarily) Modular Representation Language. The paper was entitled "An Integrated Knowledge Representation Scheme for Expert Systems".
Integrated Knowledge Representation The requirement exists in Expert Database Systems for a knowledge representation scheme that can combine relational data, class hierarchies and rules into a single integrated structure. P. Russell and A. Bracher (Deductive Systems Ltd, U.K.) presented "An Integrated Knowledge Representation Scheme for Expert Database Systems". They described the knowledge representation scheme used in the Fact System. The system extends the relational model by combining it with a class membership network. This generic data is at the heart of the Fact System's power, and the new features of the system are all ultimately attributable to this.
Design Tasks Analytical and Interactive Design In "An Expert System for Analytical and Interactive Design of Control Systems" G.K.H. Pang and J-M Boyle (Cambridge University, U.K.) proposed that an expert system can work interactively with a designer, to solve analytical control engineering design problems. They considered how to structure a design problem, and how to encode design expertise as frames. They explained how these ideas are applied to the design of multi variable control systems, a non-trivial, interactive, analytical design task. They concluded by discussing how expert systems can facilitate knowledge transfer. and act as intelligent front ends to a large engineering design package.
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Expert Systems in Design A. Gairola (Digital Equipment Corporation, F.R.G.) presented "An Application of Expert Systems in Design". He described the required features of an Expert System for Design for Assembly (DFA) and partly a strategic and conceptual approach to create it. DFA is the technique to design products with ease of assembly in mind. As an example he noted that the greatest potential for minimising the complexity and cost of realising a Flexible Assembly Workstation based on robots for assembling a particular product cannot be found in robots; rather it is achieved by designing the product for easy assembly on robotised workstations. Gairola pointed out that the main objective of building an expert system is to provide designers with a tool that requires minimum effort to create such designs.
Medical Expert Systems Diagnostic and Therapeutic Aid A. Giron and P. le Beux (Universit~ de Technologie de Compi6gne, France) presented "An Expert System for Diagnostic and Therapeutic Aid for the Depressive States". They described how the system helps the non-specialist to precisely use the various classifications of the disease by asking him simple questions which are interpreted by an expert system. The system is organised in three phases: the positive diagnostic, the computerised patient profile, the anti-depressor treatment. They explained that the system is presently in the testing phase and will then be evaluated by a panel of psychiatrists and general practitioners.
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(Hospital de la S.S. "La Paz", Spain) presented "A System for Knowledge Induction and Protocol Management Aid in Oncology". They described SKIPMAO, a knowledge-based system to aid the handling and use of voluminous clinical records and to simulate the logical inference processes doctors go through in oncology therapy, both in their practice and research. Leukaemia Diagnosis P.L. Alvey (Imperial Cancer Research Fund, U.K.) and M.F. Greaves (Leukaemia Research Fund Centre, U.K.) described in "Development of a High Performance System for Leukaemia Diagnosis" a program that analyses the test results and is based entirely on the expertise of one immunologist (M. F. Greaves). They explained that the most difficult part of the task was the development of a well integrated specification for the problems of the domain, and this required many cycles of trial and error. They pointed out that the system is still being refined but already simulates the expert's opinion in the great majority of cases. Will Expert Systems Be Safe
Knowledge Induction
It is predicted that in the near future expert systems will be commonly owned by industrial, commercial and government organisations. The general public are identified as one of the possible user populations of such systems. In "Will Expert Systems Be Safe" D. Diaper (University College London, U.K.) presented an analysis of the likely development of expert systems and intelligent interfaces. The developments were discussed with a view to making such systems as safe as possible. Evidence from dialogues between users and a simulated plausible expert system with an intelligent interface were presented.
A traditional field in the application of artificial intelligence is that of "automatic diagnosis" or "diagnostic aids". Less work has been done in the area of therapeutic decision-making. A. Vi~a Cast~eiras and G. Fern~ndez FernSndez (E.T.S. Ingenieros Telecommunicacion), and J. Felih
The Proceedings of the Second International Expert Systems Conference can be ordered from Learned Information Ltd., Woodside, Hinksey Hill, Oxford 0X1 5AU, England or Learned Information, Inc., 142 Old Marlton Pike, Medford, NJ 08055, U.S.A. ISBN 0 904933 563. 586 pages.