Mildred L. G. Shaw

Knowledge acquisition tools based on personal construct psychology

Knowledge acquisition research supports the generation of knowledge-based systems through the development of principles, techniques, methodologies and tools. What differentiates knowledge-based system development from conventional system development is the emphasis on in-depth understanding and formalization of the relations between the conceptual structures underlying expert performance and the computational structures capable of emulating that performance. Personal construct psychology is a theory of individual and group psychological and social processes that has been used extensively in knowledge acquisition research to model the cognitive processes of human experts. The psychology takes a constructivist position appropriate to the modelling of human knowledge processes, but develops this through the characterization of human conceptual structures in axiomatic terms that translate directly to computational form. In particular, there is a close correspondence between the intensional logics of knowledge, belief and action developed in personal construct psychology, and the intensional logics for formal knowledge representation developed in artificial intelligence research as term subsumption, or KL-ONE-like, systems. This paper gives an overview of personal construct psychology and its expression as an intensional logic describing the cognitive processes of anticipatory agents, and uses this to survey knowledge acquisition tools deriving from personal construct psychology.

Concept maps as hypermedia components

Concept mapping has a history of use in many disciplines as a formal or semi-formal diagramming technique. Concept maps have an abstract structure as typed hypergraphs, and computer support for concept mapping can associate visual attributes with node types to provide an attractive and consistent appearance. Computer support can also provide interactive interfaces allowing arbitrary actions to be associated with nodes such as hypermedia links to other maps and documents. This article describes a general concept mapping system that is open architecture for integration with other systems, scriptable to support arbitrary interactions and computations, and cutomizable to emulate many styles of map. The system supports collaborative development of concept maps across local area and wide area networks, and integrates with World-Wide Web in both client helper and server gateway roles. A number of applications are illustrated ranging through education, artificial intelligence, active documents, hypermedia indexing and concurrent engineering. It is proposed that concept maps be regarded as basic components of any hypermedia system, complementing text and images with formal and semi-formal active diagrams.

KITTEN: knowledge initiation and transfer tools for experts and novices

Abstract This paper gives a state-of-the-art report on the use of techniques based on personal construct psychology to automate knowledge engineering for expert systems. It presents the concept of knowledge support systems as interactive knowledge engineering tools, states the design criteria for such systems, and outlines the structure and key components of the KITTEN implementation. KITTEN includes tools for interactive repertory grid elicitation and entailment analysis that have been widely used for rapid prototyping of industrial expert systems. It also includes tools for text analysis, behavioral analysis and schema analysis, that offer complementary and alternative approaches to knowledge acquisition. The KITTEN implementation integrates these tools around a common database with utilities designed to give multiple perspectives on the knowledge base.

New directions in the analysis and interactive elicitation of personal construct systems

The computer elicitation and analysis of personal construct systems has become a technique of great interest and wide application in recent years. This paper takes the current state of the art as a starting point and explores further developments that are natural extensions of it. The overall objective of the work described is to develop man-computer symbiotic systems in which the computer is a truly dialectical partner to the person in forming theories and making decisions. A logical model of constructs as predicates applying to elements is used to develop a logical analysis of construct structures and this is contrasted with various distance-based clustering techniques. A grid analysis program called ENTAIL is described based on these techniques which derives a network of entailments from a grid. This is compared and contrasted with various programs for repertory grid analysis such as INGRID, FOCUS and Q-Analysis. Entailment is discussed in relation to Kellys superordination hierarchy over constructs and preference relations over elements. The entailment analysis is extended to rating-scale data using a fuzzy semantic model. The significance of Kellys notion of the opposite to a construct as opposed to its negation is discussed and related to other epistemological models and the role of relevance. Finally, the interactive construct elicitation program PEGASUS is considered in terms of the psychological and philosophical importance of the dialectical processes of grid elicitation and analysis, and recommendations are made about its generalization and extension based on the logical foundations described. Links are established between the work on repertory grids and that on relational data bases and expert systems.

Comparing conceptual structures: consensus, conflict, correspondence and contrast

One problem of eliciting knowledge from several experts is that experts may share only parts of their terminologies and conceptual systems. Experts may use the same term for different concepts, use different terms for the same concept, use the same term for the same concept, or use different terms and have different concepts. Moreover, clients who use an expert system have even less likelihood of sharing terms and concepts with the experts who produced it. This paper outlines a methodology for eliciting and recognizing such individual differences. It can then be used to focus discussion between experts on those differences between them which require resolution, enabling them to classify them in terms of differing terminologies, levels of abstraction, disagreements, and so on. The methodology promotes the full exploration of the conceptual framework of a domain of expertise by encouraging experts to operate in a “brain-storming” mode as a group, using differing viewpoints to develop a rich framework. It reduces social pressures forcing an invalid consensus by providing objective analysis of separately elicited conceptual systems.

Eliciting knowledge and transferring it effectively to a knowledge-based system

The knowledge acquisition bottleneck impeding the development of expert systems is being alleviated by the development of computer-based knowledge acquisition tools. These work directly with experts to elicit knowledge, and structure it appropriately to operate as a decision support tool within an expert system. However, the elicitation of expert knowledge and its effective transfer to a useful knowledge-based system is complex and involves diverse activities. The complete development of a decision support system using knowledge acquisition tools is illustrated. The example is simple enough to be completely analyzed but exhibits enough real-world characteristics to give significant insights into the processes and problems of knowledge engineering. >

Using different communication media in requirements negotiation

Contrary to traditional wisdom, the authors found that, when it comes to requirements negotiations, groups meeting face-to-face perform no better than those using video conferencing and computer support. Furthermore, their study identified a particular distributed group configuration that significantly improved performance and was more conducive to negotiations than face-to-face meetings.

Induction of inference rules for expert systems

Abstract Many of the decision-making processes of experts may be represented in terms of the fuzzy sets that correspond to their analysis of situations in terms of entities and their relationships. The elicitation of these fuzzy sets from experts can be carried out automatically by computer-based interview techniques. From this data the inference relations used in decision may be derived and encoded for an expert system shell. This paper analyses logical cluster-analytic techniques for inducing these inference relationships and gives examples of their applications to elicited data. The relations induced involve trade-offs between fuzzy truth values and the probability of their being correct. An information-theoretic measure of the uncertainty reduction due to a hypothesized relation is used to determine the optimum trade-off and to compare hypotheses.

An Interactive Knowledge-Elicitation Technique Using Personal Construct Technology

The initial success of expert system (ES) developments (Gevarter, 1983; Michie, 1979; Reitman, 1984) and the development of a number of reasonably domain-independent software support systems for the encoding and application of knowledge (Hayes-Roth et al., 1983) have opened up the possibility of widespread usage of ESs. In particular, the Japanese Fifth Generation Computing System (FGCS) development program (Gaines, 1984; Moto-oka, 1982) assumes this will happen and is targeted on knowledge processing rather than information processing. However, what Feigenbaum (1980) terms knowledge engineering, the reduction of a large body of knowledge to a precise set of facts and rules, has already become a major bottleneck impeding the application of ESs in new domains. We need to understand more about the nature of expertise in itself (Hawkins, 1983) and to be able to apply this knowledge to the elicitation of expertise in specific domains.

From timesharing to the sixth generation: the development of human-computer interaction. Part I

Abstract The human-computer interface is increasingly the major determinant of the success or failure of computer systems. It is time that we provided foundations of engineering human-computer interaction (HCI) as explicit and well-founded as those for hardware and software engineering. Computing technology has progressed through a repeated pattern of breakthroughs in one technology, leading to its playing a key role in initiating a new generation. The basic technologies of electronics, virtual machines, and software have gone through cycles of breakthrough, replication, empiricism, theory, automation and maturity. HCI entered its period of theoretical consolidation at the beginning of the fifth generation in 1980. The lists of pragmatic dialog rules for HCI in the fourth generation have served their purpose, and effort should now be directed to the underlying foundations. The recently announced sixth-generation computer system (SGCS) development program is targeted on these foundations and the formulation of knowledge science. This paper surveys the development of HCI and related topics in artificial intelligence; their history, foundations, and relations to other computing disciplines. The companion paper surveys topics relating to future developments in HCI.