ALBERT

Notes: In this paper, I present an architecture for generating extended text. This architecture is implemented in a system, Salix, which incrementally generates natural language texts whose structure is derived from the domain structure of the subject matter. The architecture is composed of data-driven, domain-independent strategies for producing increments of text. The strategies include metastrategies that combine or choose among all strategies that are applicable at each increment or decide what to do if no strategy applies. Salix's capabilities are demonstrated in generating texts, in the domains of houses and families, that are comparable to descriptions elicited from human speakers. Salix has also been utilized to generate texts about text style (Germain 1991). The approach to text generation presented here is compared to others in the literature along the dimensions of local organization, coherence, focusing, and domain independence. An argument is made for the approach presented here that locally organizes and incrementally generates coherent text.

Notes: A story generation system based on dynamics of the mind is presented. Semantic theories until now avoided discussing a linkage of language with encyclopedic human knowledge. This paper attacks the problem of how to make clear the complicated, wide-ranging dynamics of the mind and how to connect it to language.First, the background of this study is shown, in which our model of the mind, with both five levels along the concept formation process and eight domains according to the contents of mental activities, is surveyed.Based on this model, then, the dynamics of mind are discussed, along an Aesop fable. A unit of data processing in the mind is called a “module,” and the mental dynamics are considered as a chain activation of those modules, represented by a dynamic network. Next, a method for story generation is discussed. Propositional information of a sentence is embedded in a slot of activated, frame-structured modules, and the discourse structure of a generated story basically depends on the dynamic network. Both the chain activation and the generation processes are verified by experiments.Lastly, residual problems of our research, a comparison with related research, and its applications are discussed.This case study would be expected to give a basis to integrated systems for problem solving, natural language and image understandings, their generations, and intelligent robots.

Notes: Looking to the future, generators will have more knowledge of language and will have to deal with inputs that are very rich in information. As a result, several problems will become more acute, including selecting what to say at the subproposition level and dealing with interaction among goals and dependencies among choices. This paper explains how these problems arise and why they are hard to handle within traditional architectures for generation. It also discusses why these issues have not been well addressed, including the current lack of demanding applications, excessive emphasis on linguistic traditions, the use of reverse engineering to determine generator inputs, and the tendency to research only one issue at a time.

Notes: The ability to reuse existing plans to solve new planning problems can enable a domain-independent planner to improve its average case efficiency by exploiting the problem distribution and avoiding repetition of planning effort. The pay-off from plan reuse, however, crucially depends on finding effective solutions to two important underlying control problems: (i) controlling the retrieval of an appropriate plan and mapping to be reused in a new situation, and (ii) controlling the modification (refitting) of the retrieved plan so as to minimize perturbation to the applicable parts of the plan. This paper is concerned with the development of efficient domain-independent solutions to these two problems. For the retrieval, it provides a domain independent similarity metric that utilizes the plan causal dependency structure to estimate the utility of reusing a given plan in a new problem situation. For the refitting, it presents a minimum-conflict heuristic, again based on the causal dependency structure of the plan, to conservatively control the modification. The paper also discusses the implementation and evaluation of these strategies within the PRIAR plan modification framework.

Notes: Common sense sometimes predicts events to be likely or unlikely rather than merely possible. We extend methods of qualitative reasoning to predict the relative likelihoods of possible qualitative behaviors by viewing the dynamics of a system as a Markov chain over its transition graph. This involves adding qualitative or quantitative estimates of transition probabilities to each of the transitions and applying the standard theory of Markov chains to distinguish persistent states from transient states and to calculate recurrence times, settling times, and probabilities for ending up in each state. Much of the analysis depends solely on qualitative estimates of transition probabilities, which follow directly from theoretical considerations and which lead to qualitative predictions about entire classes of systems. Quantitative estimates for specific systems are derived empirically and lead to qualitative and quantitative conclusions, most of which are insensitive to small perturbations in the estimated transition probabilities. The algorithms are straightforward and efficient.

Notes: When Horn clause theories are combined with integrity constraints to produce potentially refutable theories, Seki and Takeuchi have shown how crucial literals can be used to discriminate two mutually incompatible theories. A literal is crucial with respect to two theories if only one of the two theories supports the derivation of that literal. In other words, actually determining the truth value of the crucial literal will refute one of the two incompatible theories.This paper presents an integration of the idea of crucial literal with Theorist, a logic-based system for hypothetical reasoning. Theorist is a goal-directed nonmonotonic reasoning system that classifies logical formulas as possible hypotheses, facts, and observations. As Theorist uses full clausal logic, it does not require Seki and Takeuchi's notion of integrity constraint to define refutable theories. In attempting to deduce observation sentences, Theorist identifies instances of possible hypotheses as nomological explanations: consistent sets of hypothesis instances required to deduce observations. As multiple and mutually incompatible explanations are possible, the notion of crucial literal provides the basis for proposing experiments that distinguish competing explanations.We attempt to make three contributions. First, we adapt Seki and Takeuchi's method for Theorist. To do so, we incrementally use crucial literals as experiments, whose results are used to reduce the total number of explanations generated for a given set of observations. Next, we specify an extension which incrementally constructs a table of all possible crucial literals for any pair of theories. This extension is more efficient and provides the user with greater opportunity to conduct experiments to eliminate falsifiable theories. A prototype is implemented in CProlog, and several examples of diagnosis are considered to show its empirical efficiency. Finally, we point out that assumption-based truth maintenance systems (ATMS), as used in the multiple fault diagnosis system of de Kleer and Williams, are interesting special cases of this more general method of distinguishing explanatory theories.

Notes: When trying to understand a speaker's argument, it is necessary to determine what her claim is and what evidence she provides for it. It is necessary, therefore, to be able to recognize evidence relations in terms of the speaker's beliefs. This paper describes an implementation of an evidence oracle, which tests for evidence between statements and builds a model of the speaker based on the evidence relations found. This implementation is intended to be an advance in the development of practical discourse analysis systems, proposing a basis for verifying certain relationships between utterances. Another contribution of the work is a stratified speaker model which allows for varying levels of acceptance of beliefs attributed to the speaker. Integration of the implemented evidence oracle into a full discourse analyser is presented, together with output illustrating the analysis for several sample arguments. Some extensions of this approach for plan inference are also discussed.Lorsque l'on essaie de comprendre l'argument d'un locuteur, il importe de déterminer la nature de sa prétention et le type d'évidence qui l'accompagne. Par conséquent, il est nécessaire de pouvoir distinguer des relations d'évidence les croyances du locuteur. Cet article décrit la mise en oeuvre d'un oracle qui recherche l'évidence entre des énoncés et construit un modèle du locuteur en fonction des relations d'évidence constatées. Cette mise en oeuvre propose une base pour vérifier certaines relations entre des énoncés; elle se veut une contribution au développement d'un système pratique d'analyse du discours. Une autre contribution de cette recherche est l'élaboration d'un modèle de locuteur stratifyé qui tient compte de niveaux variables d'acceptation des croyances attributeés au locuteur. l'intégration de l'oracle d'évidence sous forme d'analyseur de discours est présentée, ainsi que des illustrations de l' analyse de plusieurs arguments types. Une extension de cette approche à l'inférence de plans est également discutée.

Notes: The ability of a biological organism to visually track a perceptually significant feature in its environment has been argued to be an important feedback mechanism guiding locomotion. This paper analyzes the constraints available from the visual motion stimuli in the context of tracking. Our aim is to show that the act of tracking simplifies the decoding of egomotion parameters from motion stimuli. The constraints obtainable under tracking are utilized to analyze a possible egomotion decoding strategy for a binocular robot eye system, modeled after the human ocular tracking (smooth pursuit) mechanism. The main result of the paper is in the derivation of a closed-form solution of the egomotion parameters using feedback information concerning the movement of the tracking motors over time. The theoretical results are verified by experiments. We believe that the active tracking approach presented here is a more simple, practical, and manageable technique in a robot navigation setting, compared to passive methods.

Notes: This paper considers computer programs that purport to do inference. It finds the essence of their reasoning ability to reside in a particular relationship which exists between the computations described by the texts of those programs and machine-independent formal representations of the theories in which they are said to reason. The principal novelties in the treatment of this question are the use of explicit “abstraction functions” between states of a computation and sets of sentences of a theory, and the notion of global “inference relations” which characterize the set of all inferences of which a system is capable. The central result of the paper is an “arrow-theoretic” characterization of the concept of a knowledge representation, along with the related concept of a knowledge representation realization. The notions of equivalence and subsumption for knowledge representations are defined, as well as equivalence of knowledge representation realizations. Finally, important issues of expression evaluation and control are addressed. The paper concludes with a slogan: “The AI is in the arrows.”Cet article traite des programmes informatiques qui prétendent faire de ľinférence. Ľauteur constate que ľessentiel de leur capacityé de raisonnement réside dans la relation particulière qui existe entre les calculs décrits par les textes de ces programmes et les représentations formelles non liées à un type de machine des théories dans le cadre desquelles ils sont supposés raisonner. Les principales nouveautés dans le traitement de cette question sont ľutilisation de fonctions ?abstraction explicites éntre les etats ?un calcul et les ensembles de phrases ?une théorie, et la notion de relations ?inférence globales qui caractérisent ľensemble de toutes les inférences dont un système est capable. Le principal résultat de cet article est une caractérisation du concept de la représentation des connaissances, ainsi que du concept connexe de la réalisation de la représentation des connaissances. Les notions ?équivalence et de sous-somption pour la représentation des connaissances sont définies, ainsi que ľéquivalence des réalisations de la représentation des connaissances. Enfin, des questions importantes comme ľanalyse et le contrǒle ?expressions sont traitées.

Notes: The use of a single grammar in natural language parsing and generation is most desirable for a variety of reasons, including efficiency, perspicuity, integrity, robustness, and a certain amount of elegance. These characteristics have been noted before by several researchers, but it was only recently that more serious attention started to be paid to the problem of creating a bidirectional system for natural language processing. In this paper we discuss a somewhat more radical version of the problem: given a parser for a language, can we reverse it so that it becomes an efficient generator for the same language? Furthermore, since both the parser and the generator are based upon the same grammar, are there any normalization conditions upon the form of the grammar that must be met in order to assure the maximum efficiency of the reversed program? Can other grammars be transformed into the normal form? We describe the results of an experiment with PROLOG-based logic grammar which has been derived from a substantial-coverage string grammar for English. We present an alogorithm for automated inversion of a unification parser into an efficient unification generator, using the collections of minimal sets of essential arguments for predicates. We discuss the scope of the present version of the algorithm and then point out several possible avenues for extension. We also outline a preliminary solution to the question of grammar's “normal form” and suggest a handful of normalizing transformations that can be used to enhance the efficiency of the generator. This research interacts closely with a Japanese-English machine translation project at New York University, for which the first implementation of the inversion algorithm has been prepared.

Notes: Halperri argues for alternative non-Bayesian approaches to uncertainty based on problems he perceives in the Bayesian approach. In particular, he argues for a distinction between degrees of belief and statistical statements (based on the concept of random sampling). In this response I show that there is no difference between these two concepts in the Bayesian framework, and that the replacement of variables by constants in probabilistic predicate calculus expressions is valid, despite Halpern's objections. The main reason for his rejection of the simpler approach is that he does not condition his belief statements on the evidence used to form these beliefs, and so gets into trouble when new evidence is received. This failure to properly take evidence into account invalidates most of his other criticisms. While I approve of his call for more formal rigor in representing Bayesian practice, his claim to have provided a semantics is misleading – what he has provided is not operational.

Notes: A hierarchical planning system achieves efficiency by planning with the most important conditions first, and considering details later in the planning process. Few attempts have been made to formalize the structure of the planning knowledge for hierarchical planning. For a given domain, there is usually more than one way to define its planning knowledge. Some of the definitions can lead to efficient planning, while others may not. In this paper, we provide a set of restrictions which defines the relationships between a non-primitive action and its set of subactions. When satisfied, these restrictions guarantee improved efficiency for hierarchical planning. One important feature of these restrictions is that they are syntactic and therefore do not depend on the particular structure of any plan. Along with these restrictions, we also provide algorithms for preprocessing the planning knowledge of a hierarchical planner. When used during planning, the preprocessed operator hierarchies can enable a planner to significantly reduce its search space.

Notes: Abstract: Many organizations today have an interest in communications networks, either as users of public networks or as operators of their own private networks. Thus, the management of communications networks has become an important issue in the communications industry. The network design task is fundamental to the whole notion of network management; however, with the rapid rate of change in network technology and the emergence of highly sophisticated network users, network design has become an increasingly complex problem.The purpose of this paper is to describe a development effort which incorporates expert systems techniques to treat one aspect of the network design problem—the initial planning and design of a network prior to implementation. The research effort was concerned with developing an expert system for Amdahl Communications Products which could be used by sales engineers in designing wide area networks to meet specified customer requirements. The system treats both the topological design problem and the component configuration problem.

Notes: Abstract: The rapid growth in the use of expert systems has led to widespread interest in techniques for their evaluation, which includes verification and validation. Evaluation techniques in the software engineering community are well established but there are different opinions about the effectiveness of transferring software engineering methodologies to expert systems. This paper outlines some of the issues involved in evaluating expert systems and cites almost 200 significant papers on the topic. We present it with the expectation that it will help both new and established researchers become acquainted with the literature of an important and growing field.

Notes: Abstract: This paper describes some of the problems encountered in developing a user interface for a commercial expert system. The emphasis is on the practical side of interface implementation while attempting to follow the many guidelines presented in the literature.

Notes: Abstract: The need to integrate knowledge-based systems (KBS) with mainstream data processing (DP) systems is increasingly recognised. It is also recognised that there is no ideal mode of KBS integration: different types of problem call for different modes of integration. Many large organisations are now facing a serious problem in the operation of their existing DP systems. This paper focuses on the problem of providing intelligent support to the (often inexperienced) terminal users of complex mainframe systems—but without initiating any significant changes to the existing DP environment. Over the past few years we have been attempting to evolve a solution to this type of problem that is satisfactory from both a human and a software engineering perspective. This paper outlines the previous work and considerations underlying our current approach. Starting from a purely mainframe-based mode of integration, this has entailed locating an increasing number of an integrated KBS-DP system's components onto a front-end workstation. In our current solution, both user interface and KBS modules reside on a workstation linked to the (unchanged) mainframe environment. The key element of this approach is terminal operator emulation: a KBS-controlled 'script’ facility on a workstation which emulates the flexible keyboard behaviour of an experienced mainframe terminal user interacting with an existing DP system. The software tools and techniques employed in implementing this solution are discussed and details of a large operational system are presented as an example application.

Notes: Abstract: The aim of this paper is to describe a system whereby an intensive care unit patient's condition can be monitored and assessed over time using mostly blood gas analysis data. The first six sections analyse some major temporal reasoning approaches (with limited examples from other related areas) with the aim of selecting one for the task at hand. The last sections describe the PONJIP temporal blood gas analysis expert system with its main components, including user interfaces customised to the doctor's requirements. Since the overall aim of this paper is to describe an expert system used for the evaluation of the possible contribution of temporal medical reasoning from blood gas data, research specific to other application areas or data will not be covered here.

Notes: Abstract: Solving the customer's LAN/WAN interconnect problem is difficult because of the need to explore many possible configurations (e.g. bridging/routing, packet/channels) and then to choose the best configuration using economic, performance and other criteria. The rapid introduction of new standards, protocols and products to the networking field brings additional complications to the solution and can cause confusion when configuring a network. ALCA is intended to generate all feasible LAN/WAN configuration possibilities automatically and to pick the most appropriate solution to solve the customer's problem, while specifically addressing open systems interconnection (OSI) standards. Matching communications protocols while searching all possible configurations is notoriously slow even on a computer. We show how the search speed can be significantly improved by using expert system knowledge compilation, a computer-aided software engineering (CASE) technique. ALCA is based on a centrally updated knowledge base of various local area networking products and their interconnect possibilities. ALCA also allows querying to find out protocol interfaces supported by a particular product/service. Finally, it includes a graphic user interface and context-sensitive menus to reduce user information load. ALCA is intended to be used by the field personnel involved in pre-sales support, by the data communication product managers, and as an educational tool for novice communication product managers.

Notes: Abstract: Artificial intelligence has emerged from the toy problem world and is being applied to real domains in a more general way, the existence of several large application systems supporting the belief that a generation of smarter and more general systems will be developed. However, a new problem, sometimes referred to as the fusion problem, has been identified, which acts to restrict the development of such systems. This paper explains the nature of the problem, and by examining a proposed expert system in economics (ESE), discussing three approaches to a prototype ESE and the problems associated with them, draws some conclusions with regard to data fusion and expert co-operation.

Notes: Abstract: This paper presents work undertaken as part of a project concerned with the development of a fully automated industrial radiographic inspection system, based on both conventional image-processing techniques for the detection and analysis of defects in the radiographic image, and intelligent knowledge-based (1KB) techniques for the classification and evaluation of defect data against the quality assurance requirements of the inspection process. In this paper the 1KB defect classification system is presented. This system is based on a hierarchical frame-based knowledge representation and a backward-chaining production rule system. Examples of the frame structures, frame taxonomies and the data-driven procedures, which maintain the knowledge base are given, along with an outline of the defect classification rules and the inference mechanism for dealing with uncertainty by means of confidence factors.

Notes: Abstract: The excessive time devoted to the development, testing and maintenance of expert systems (ESs) needs to be reduced radically. What is needed is general-purpose software that can interlace the extracting, structuring, testing, and encoding of knowledge gained from debriefing the expert in any field. LAPS (Logic Aids for Problem Solving) is just such a program and has been successfully used to produce an ES in the domain of submarine diving officers. This automatically-encoded ES was produced by each expert entering his responses to the LAPS series of strategic-induction, AI-jargon-free queries. Currently, the LAPS prototype has four core sessions or functions: (1) the initial or sample-solution session; (2) the dechunking or hidden-knowledge session; (3) the alternatives or completeness-testing session; and (4) the automatic rule-production session. After any session the interviewee can use the fourth function of LAPS to produce frame-laden rules (in M.I, for now; later, in CLIPS). These rules can of course be used to carry out consultation sessions, though fewer of these are needed. LAPS has itself been translated from M.I to C to provide a very fast program on an almost universally available platform — the microcomputer. In accord with the overall technical approach to this project, other successful offline rigorous interviewing functions are being added to LAPS. Other code additions pertain to (a) graphical and other user-friendly reasoning-aid enhancements; (b) a series of simpler follow-up queries; and (c) the fleshing out of many stubs, or functions having intermediate results but as yet no processing.

Notes: Abstract: This paper describes a shell for cooperating expert systems that has been developed at the University of Porto. The main goal of this shell is two-fold: to generate a community of cooperative knowledge-based systems and to develop several special reasoning techniques which can be used under a distributed and cooperative paradigm. UPShell is able to convert a set of generated intelligent systems (ISs) into a community of cooperative ISs. In this first version it is already possible to generate different intelligent systems which are able to run ‘simultaneously’ as separate Unix processes and, using a message-passing mechanism, to communicate among themselves. They can be set to pursue an overall goal in a cooperative way. Moreover, several tasks can be given to each IS to be solved simultaneously, and the IS can switch from task to task according to dynamic priorities reflecting the urgency attached to the specific sub-tasks that emerge. The shell described here may also be used to test, within a distributed environment, some time-bounded reasoning techniques that are presently being developed. The paper has three main parts: a general overview of the UPShell (Section 1); a tutorial explaining, by means of examples, how to use the package (Section 2); and, finally, some considerations on the reasoning techniques used and future improvements (Sections 3–5).

Notes: Book reviewd in this article:Expert Systems in Production and Services II: From Assessment to Action?Thomas Bernold, Ulrich Hillenkamp (Eds.)Expert Systems: Human Issues. D. Berry, A. Hart.Prolog and its Applications: A Japanese Perspective. Fumio Mizuguchi (Ed.)

Notes: Abstract: A mechanism for tracing the utilization of rules in expert systems during periods of practical usage is proposed. Statistics related to the utilization of each rule help the designer to re-evaluate the appropriateness of each rule, so that over-utilized rules may be expanded and unnecessary ones deleted. By incorporating such a mechanism, the efficiency of maintaining and updating expert systems is improved.

Notes: Abstract: Expert system shells are discussed as very-high-level programming languages for knowledge engineering. Based on a category/domain distinction for expert systems the concept of expert system shells is explained using seven classifications. A proposal for a shell-development policy is sketched. The conclusions express concern about current over-emphasis on graphical interfaces.

Notes: Abstract: This article describes the development of a knowledge-based system (KBS) for guiding both technical and non-technical managers in estimating the risks inherent in proposed KBS development projects. The work described here is part of an ongoing research project studying the use of KBS both to teach and to do KBS development. So far, as part of this research project, over the past two years close to 150 non-technical and technical full-time business managers have developed some 75 KBS prototypes in conjunction with an MBA course in strategic planning. Based on replies to a survey of this test group, 17% of the KBS developed were reportedly used at work, 14% led to promotions, pay raises, or new jobs, and 14% led to participation in other KBS development projects at work. All but two of the survey respondents reported that their work on the KBS development project led to a substantial increase in their job knowledge or performance. The KBS work described here extends research work described by Cullen and Bryman [1988], Slagle and Wick [1988], Cohen and Howe [1988], Dologite [1988, 1989], and Mockler [1989(A) and (B)].

Notes: Abstract: The sophisticated nature of new production facilities means more complex maintenance units and costly breakdowns. For users of high tech machinery, the efficiency of their maintenance services is becoming an increasingly important factor, and for manufacturers, the maintainability of their equipment they sell is an element that has to be taken into account in their battle for market share. Troubleshooting Expert Systems (TES) are one possible means of improving maintenance capability and maintenance units. Surveying cases of success or failure that the authors have witnessed themselves or come across in the literature, they propose a checklist of seven questions to be considered at the outset of TES development, which deal with the human, managerial and organisational aspects of TES.

Notes: Abstract: This paper deals with the issue of knowledge elicitation for expert systems. Specifically, it looks at the requirements of the knowledge elicitation process and the suitability of structured methods from systems analysis to carry out part of the elicitation task. The techniques of data flow analysis, entity-relationship analysis and entity-life cycle analysis are used to structure the data associated with the expert task. The methods proposed lay emphasis on the definition of limited data sets at the boundary of the explicit knowledge base and the identification of status attributes to model the control of activation of ‘processes’ within the knowledge base. Attention is also paid to the relationship between the resulting logical model, and two popular methods of knowledge representation, namely, Production Systems and Frames.

Notes: Abstract: Despite their potential advantages, robots are not used much by industry andlor services. One of the major reasons for this situation is the limitations of robots, especially their lack of ‘intelligence”. Artificial intelligence and expert systems technologies can help in this case. This paper describes the potential contribution of expert systems to the decision making capabilities of robots and to decisions regarding robots. The major potential contribution of expert systems is in the automation of the error recovery process. Specifically, when something is going wrong in the robot itself or in its work environment, an automated corrective action is needed. Today's technology is capable of economically handling some of the activities in the process (e.g. interpretation of signals from sensors, diagnosis of what is wrong and suggestions for remedies). The AI technology is still not capable in most cases (at least in an economical manner) of actually restoring the robot's operations. The paper also gives examples of several experimental expert systems in the robotic field.

Notes: Knowledge-Based Systems: Markets, Suppliers and Products, Tim Johnson et al.The European Market for Expert Systems, Artificial Intelligence Systems and Expert Systems Used in Medical Laboratory Applications

Notes: Abstract: The intended purpose of this article is twofold: to study techniques for uncertainty management in expert systems, particularly the Dempster-Shafer theory of belief; and to use this method in the construction of an expert system for the field of forecasting and marketing management. Compared with the probabilistic approach, which can only deal with singleton possibilities, the Dempster-Shafer approach proves to be superior because it provides the ability to deal with sets of possibilities. Since market analysis and forecasting always have a strong element of uncertainty associated with them, and since, in general, we consider a combination of several different forecasting techniques for planning our marketing strategies, the Dempster-Shafer approach is particularly suitable. Here we present a short introduction to this theory, briefly discuss the domain of application (selection of forecasting techniques for marketing planning), discuss the interesting components of our expert system, and analyze our experiences in applying the theory to this domain.

Notes: Abstract: Current methodologies for choosing problems suitable for implementation as IKBS's are not appropriate for the retail industry, due to singularities of the domain. In particular, they exclude from consideration a kind of system which uses Electronic Point of Sale (EPOS) data to structure unstructured managerial perceptions, but several examples of these systems have been successfully implemented. Methodologies may be more domain specific than they were thought to be, and may hold back implementations to an artificially imposed level of difficulty. Nonetheless, analysis of the level of structure found in a problem is useful, as it points out possible trouble spots, and Fuzzy/Complex analysis was felt to be the most suitable methodology for retail due to its manufacturing origins, clarity of purpose, and flexibility.

Notes: Book reviewed in this article:Expert Systems for Engineering Design, M.D. Rychener (ed.)

Notes: Abstract: This paper presents the architecture of a neural network expert system shell. The system captures every rule as a rudimentary neural network, which is called a network element (netel). The aim is to preserve the semantic structure of the expert system rules, while incorporating the learning capability of neural networks into the inferencing mechanism. These netel rules are dynamically linked up to form the rule-tree during the inferencing process, just as a conventional expert system does. The system is also able to adjust its inference strategy according to different users and situations. A rule editor is provided to enable easy maintenance of the netel rules. These components are housed under a user-friendly interface. An application

Notes: Abstract: Case-based reasoning (CBR) is a problem-solving paradigm where past experiences are used to guide problem-solving. This paradigm shows a great deal of promise for use in intelligent systems. Recent work in intelligent systems focusing on AIDS prevention reflects a growing interest in the case-based paradigm because AIDS prevention experts rely heavily on memory of previous cases when assessing subjects that exhibit AIDS-risky behaviors. If an AIDS prevention expert has seen a subject with similar AIDS-risky behavior previously, he or she is likely to draw on that experience to propose a solution to the new case at hand. This paper describes a CBR system that functions as an AIDS prevention expert. The inputs are risk behavior descriptions and the subject's test results. The system employs fuzzy mathematical algorithms to retrieve and select previous cases, thereby assessing the subject's risk.

Notes: Abstract: Many decision-aiding technologies require valid probability judgements to be elicited from domain experts. But how valid are experts' probability judgements? We describe two approaches to the assessment of quality of probability judgement—calibration and coherence—and review the research findings following from these two approaches. In many cases, expert probability judgement has been found to lack validity and this sub-optimality has largely been attributed to computational errors on the part of the expert. The preferred solution to poor validity in probability judgement has therefore been to reduce the amount of computation performed by the expert. Complex probabilities can be calculated mechanically from simple probability judgements elicited from the expert. We present evidence which suggests that this recomposition technique doesn't guarantee valid probabilities. Our explanation for this finding is that there are various problems concerned with eliciting even the simple probabilities which are necessary for subsequent recomposition. We conclude by proposing some solutions to these elicitation problems which should help ensure that probability judgements of increased validity are available to those attempting to capture subjective assessments for input into decision support systems.

Notes: Abstract: There has been a growing desire for methodological support for the development of knowledge-based systems, and the KADS methodology is probably the most widely known methodology in Europe. However, KADS has been criticised for the overhead which it places on small and medium-sized KBS projects where the risks of KBS development becoming unmanageable are relatively low. This paper describes the use of ‘pragmatic KADS’, an attempt to extract the most useful elements from the KADS methodology, in the development of the COURSE SELECTOR KBS, which assists undergraduate students to choose courses which comply with University regulations and timetabling restrictions. This KBS was built in six man-weeks. The paper describes the three major phases of a KBS project, giving a brief outline of the KADS approach to each of these stages, and then discusses the techniques which were actually used for COURSE SELECTOR. It concludes with a recommendation of techniques for future small KBS projects.

Notes: Abstract: FDAS (Fabric Defects Analysis System) is a knowledge-based system (KBS) for diagnosing defects in woven textile structures. The following major issues were considered in the design of FDAS: (1) range of applications; (2) user profiles; (3) response time requirements; (4) modularity and (5) ease of system modification and enhancements. Knowledge about defects is represented in FDAS using a hierarchy of classes, with the slots representing defect attributes, and forward chaining rules. The inferencing process is controlled by slots of another distinct class hierarchy. Inference is made more efficient by hierarchical classification of the defects with pruning. The agenda (i.e. ordered set of hypotheses) is dynamically reset using actions attached to rules. The diagnosis information—information about the causes of the defects and remedial actions to be taken—is kept separate from the rules in the knowledge base. The user interface part of the system is also independent of the knowledge base, which facilitates easier tailoring of the system to meet the needs of different users. The user interaction with FDAS is menu-based and has been designed to minimize cognitive load on the user. FDAS has been extensively evaluated by in-house individuals who are experts in the task of fabric defects analysis. It has also been demonstrated to experts from the industry and is ready for field tests.

Notes: Abstract: This paper describes the use of the explanation-based learning (EBL) machine learning technique in the practical domain of knowledge acquisition for expert systems. A knowledge acquisition tool, EBKAT (Explanation-Based Knowledge Acquisition Tool), is described, which may be used in the development of knowledge bases for diagnostic expert systems. The functioning of EBKAT attempts to combine the full potential of a domain expert's skills and the power of explanation-based machine learning techniques. The EBL component is not employed in the acquisition of the knowledge base rules but is used to justify the knowledge entered and to relate it to the knowledge already in the system. It is suggested that the EBKAT tool goes some way towards overcoming the knowledge acquisition bottleneck and results in the acquisition of knowledge which is rich in contextual information.

Notes: Abstract: Knowledge-based systems have previously been restricted to capturing the knowledge of living human experts and, in the medical domain, to delaying the onset of death in living patients. The system described in this paper overcomes both these restrictions by providing knowledge-based support for the reanimation of dead patients, who may also be domain experts.There is a well-established literature on raising the dead to life and an extensive literature on counselling patients who have undergone traumatic experiences. Examination of this literature suggests that the actual reanimation process is a relatively simple process, so the system concentrates on the counselling and care aspects. Results so far are encouraging.The next version of the system is intended to include a natural language interface to handle the English-Aramaic interpretation which is expected to be necessary for the actual reanimation process: this version will require further funding and clearance from the appropriate ethical committees. Both of these are expected to present few difficulties.The success of this system demonstrates that application of proven KBS techniques to a domain previously considered intractable can produce surprisingly fast and impressive results; to date, over 90% of system modules have been successfully tested. It is likely that this success could be replicated in other areas and this is currently the subject of further study by the authors (Rugg & Phibes 1993b).

Notes: Abstract: In this paper we present a new approach to evaluating expert systems. Our conceptual framework is based on a socio-technical model that spawned some 39 technical and contextual evaluation criteria. These socio-technical dimensions of quality are identified, defined and supported. We suggest that the approach presented here is an alternative to the restrictive verification and validation techniques that seem to be prevalent.

Notes: Book reviewed in this article:Understanding Expert Systems Using Crystal, Mary Jackson

Notes: Abstract: Knowledge engineers often find that experts’ estimates of uncertainty change from one day to the next and therefore often seem unreliable. This article explores the unreliability of probability estimates. Forty undergraduates answered 31 questions concerning the probability of daily events at two separate times. Three answer modalities were available: probability, chances and percent of the time. This paper finds that reliability decreases when answer modalities change from one time to the next. It is hypothesized that problem-solving approaches changed along with the modalities. The subjects represented a wide range in reliability, with the most reliable subjects changing answer modalities less than the unreliable subjects. These results suggest that knowledge engineers should endeavor to have experts express their uncertainty estimates using consistent modalities.

Notes: Abstract: Developing a prototype can be crucial to the eventual success of an expert system. This paper describes an evaluation of four expert system tools that can be used for prototyping. It outlines the evaluation method used and details findings, considering hardware and software requirements, tool features, support for development and consultation, and overall suitability for prototyping an expert system application.

Notes: Book reviewed in this article:The Craft of Prolog, Richard A. O'KeefeObject-Oriented Programming with Smat It al k/V, Dusko Savíc

Notes: Abstract: This article describes the integration of an expert system shell (AllRound Expert System, AR/XPS) with a Unix-based 4GL application generator (Task Flow Management, TFM). TFM supports the client-server architecture of distributed applications and provides access to several relational databases, including Informix and Oracle. A short overview of the major features of TFM is given, with special regard to characteristics relevant for the integration of an expert system. The main focus lies in the architecture of AR/XPS, which contains rule-based and frame-based knowledge representation methods and which was implemented in Prolog; the user interface is totally unified with that of TFM, so that the user sees only one system and need not be aware that an expert system is present. AR/XPS has access to all features of TFM and to any databases present, so that an expert system can take decisions according to the current status of the database. At the end of this article a description of the Knowledge Base Creator is given and some remarks are made regarding our experience with pilot applications.

Notes: Abstract: Instigating the selection of a methodological approach for the development of a knowledge-based system (KBS) should not be trivialised. This paper sets out to enlighten the reader about the needs and difficulties in comparing methodologies. In doing so, a descriptive framework is presented which allows the depiction of essential features of a methodology. This is intended to simplify the comparative study of KBSs that a knowledge engineer might be involved in.

Notes: ProKappa is an expert system tool kit developed by IntelliCorp in C using X-Windows for graphical interface. The SUN 3 or 4 version costs $9995/£7000 and $2595/£1800 for the interactive C environment. This review covers ProKappa version 1.1, installed on a colour SUN SPARC Station 1 with the minimum recommended values of 12 Mb of memory and 30 Mb of swap space. IntelliCorp can be contacted in the USA at 1975 El Camino Real West, Mountain View, CA 94040-2216 (+1 (415) 965-5500) and in the UK at 10 Jewry Street, Winchester, Hampshire SO23 8RZ (+44 (0)962 735348).

Notes: Book reviewed in this article:Integrating knowledge-based and database management systems, Ruth KerryNonmonotonic reasoning: logical foundations of commonsense Gerhard BrewkaBuilding knowledge-based systems: towards a methodology John S. EdwardsThe Rise of the Expert Company—How Visionary Companies are Using Artificial ntellig ence to Achieve Higher Productivity and Prof its, Edward Feigenbaum