An Overview of Knowledge-Acquisition and Transfer

A distributed anticipatory system formulation of knowledge acquisition and transfer processes is presented which provides scientific foundations for knowledge engineering. The formulation gives an operational model of the notion of expertise and the role it plays in our society. It suggests that the basic cognitive system that should be considered is a social organization, rather than an individual. Computational models of inductive inference already developed can be applied directly to the social model. One practical consequence of the model is a hierarchy of knowledge transfer methodologies which defines the areas of application of the knowledge-engineering techniques already in use. This analysis clarifies some of the problems of expertise transfer noted in the literature, in particular, what forms of knowledge are accessible through what methodologies. The model is being used as a framework within which to extend and develop a family of knowledge-support systems to expedite the development of expert-system applications.

[1]  Douglas B. Lenat,et al.  CYC: Using Common Sense Knowledge to Overcome Brittleness and Knowledge Acquisition Bottlenecks , 1986, AI Mag..

[2]  Tianran Wang,et al.  Knowledge Acquisition for Constructive Systems , 1985, IJCAI.

[3]  Jens Rasmussen,et al.  Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[4]  B. Gaines SYSTEM IDENTIFICATION, APPROXIMATION AND COMPLEXITY , 1977 .

[5]  William R. Swartout Knowledge needed for expert system explanation , 1899 .

[6]  Brian R. Gaines,et al.  KITTEN: Knowledge Initiation and Transfer Tools for Experts and Novices , 1987, Int. J. Man Mach. Stud..

[7]  John P. McDermott,et al.  Doing R1 with Style , 1985, CAIA.

[8]  Ryszard S. Michalski,et al.  Knowledge acquisition by encoding expert rules versus computer induction from examples: a case study , 1980 .

[9]  Brian R. Gaines,et al.  A Learning Machine in the Context of the General Control Problem , 1966 .

[10]  David Hawkins,et al.  An Analysis of Expert Thinking , 1983, Int. J. Man Mach. Stud..

[11]  John H. Boose,et al.  A Knowledge Acquisition Program for Expert Systems Based on Personal Construct Psychology , 1985, Int. J. Man Mach. Stud..

[12]  P. A. Williamson,et al.  Asymmetric neural control systems in human self-regulation. , 1984, Psychological review.

[13]  G. Klir IDENTIFICATION OF GENERATIVE STRUCTURES IN EMPIRICAL DATA , 1976 .

[14]  F ROSENBLATT,et al.  The perceptron: a probabilistic model for information storage and organization in the brain. , 1958, Psychological review.

[15]  Donald A. Norman,et al.  Twelve Issues for Cognitive Science , 1980, Cogn. Sci..

[16]  James L. Alty,et al.  Expert Systems: An Alternative Paradigm , 1984, Int. J. Man Mach. Stud..

[17]  Timothy D. Wilson,et al.  Telling more than we can know: Verbal reports on mental processes. , 1977 .

[18]  Judea Pearl,et al.  Fusion, Propagation, and Structuring in Belief Networks , 1986, Artif. Intell..

[19]  D. Broadbent,et al.  Implicit and explicit knowledge in the control of complex systems , 1986 .

[20]  Gary S. Kahn,et al.  MORE: An Intelligent Knowledge Acquisition Tool , 1985, IJCAI.

[21]  Ryszard S. Michalski,et al.  Variable Precision Logic , 1986, Artif. Intell..

[22]  Kristen Nygaard,et al.  The development of the SIMULA languages , 1978, SIGP.

[23]  John H. Boose,et al.  Rapid Acquisition and Combination of Knowledge from Multiple Experts in the Same Domain , 1985, Conference on Artificial Intelligence Applications.

[24]  Barbara Hayes-Roth,et al.  A Blackboard Architecture for Control , 1985, Artif. Intell..

[25]  Gordon Pask,et al.  Developments in Conversation Theory - Part 1 , 1980, Int. J. Man Mach. Stud..