Fuzzy sets based knowledge systems and knowledge elicitation

Abstract Fuzzy sets are adequate forms of knowledge representation when the information is uncertain due to vagueness and imprecision. Knowledge structures using fuzzy sets are similar to those implemented in non-fuzzy systems. Classical knowledge elicitation methods can be used in combination with techniques to develop membership functions. The fuzzy set representation has several advantages, including flexibility in expressing uncertain knowledge during elicitation, representation of the knowledge and its uncertainty as a unique entity, easy interfacing with classical systems, and a more robust system in ill-defined domains. These advantages result in increased system reliability.

[1]  John H. Boose,et al.  A survey of knowledge acquisition techniques and tools , 1993 .

[2]  J. Searle,et al.  Is the brain's mind a computer program? , 1990, Scientific American.

[3]  Michael Barr,et al.  The Emperor's New Mind , 1989 .

[4]  Elizabeth S. Cordingley,et al.  Knowledge elicitation techniques for knowledge-based systems , 1989 .

[5]  Waldemar Karwowski,et al.  Fuzzy data and communication in human-computer interaction: for bad or for good , 1989 .

[6]  Anna Hart,et al.  Knowledge acquisition for expert systems , 1988 .

[7]  J. St B. T. Evans.  The knowledge elicitation problem: a psychological perspective , 1988 .

[8]  J. St B. T. Evans,et al.  Human biases and computer decision-making: a discussion of Jacob et al. , 1987 .

[9]  David A. Cleaves,et al.  Cognitive Biases and Corrective Techniques: Proposals for Improving Elicitation Procedures for Knowledge-Based Systems , 1987, Int. J. Man Mach. Stud..

[10]  Jean-Lou Chameau,et al.  Membership functions II: Trends in fuzziness and implications , 1987, Int. J. Approx. Reason..

[11]  Jean-Lou Chameau,et al.  Membership functions I: Comparing methods of measurement , 1987, Int. J. Approx. Reason..

[12]  D. I. Blockley,et al.  Uncertain Inference in Knowledge‐Based Systems , 1987 .

[13]  Gavriel Salvendy,et al.  A Conceptual Framework for Knowledge Elicitation , 1987, Int. J. Man Mach. Stud..

[14]  Brian R. Gaines,et al.  An Overview of Knowledge-Acquisition and Transfer , 1987, Int. J. Man Mach. Stud..

[15]  Larry J. Eshelman,et al.  MOLE: A Tenacious Knowledge-Acquisition Tool , 1987, Int. J. Man Mach. Stud..

[16]  Gavriel Salvendy,et al.  Strategies and biases in human decision-making and their implications for expert systems , 1986 .

[17]  H. Trussell,et al.  Constructing membership functions using statistical data , 1986 .

[18]  Donald A. Waterman,et al.  A Guide to Expert Systems , 1986 .

[19]  John H. Boose,et al.  Expertise transfer for expert system design , 1986 .

[20]  Terry Winograd,et al.  Understanding computers and cognition , 1986 .

[21]  Hans-Jürgen Zimmermann,et al.  Fuzzy Set Theory - and Its Applications , 1985 .

[22]  Gary S. Kahn,et al.  Strategies for Knowledge Acquisition , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[23]  C. V. Negoiţă,et al.  Expert systems and fuzzy systems , 1985 .

[24]  I. B. Turksen,et al.  A model for the measurement of membership and the consequences of its empirical implementation , 1984 .

[25]  D. I. Blockley,et al.  Measures of uncertainty , 1983 .

[26]  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.

[27]  D. Dubois,et al.  Unfair coins and necessity measures: Towards a possibilistic interpretation of histograms , 1983 .

[28]  L. Zadeh.  The role of fuzzy logic in the management of uncertainty in expert systems , 1983 .

[29]  V. B. Kuz'min.  A parametric approach to description of linguistic values of variables and hedges , 1981 .

[30]  Didier Dubois,et al.  Fuzzy sets and systems ' . Theory and applications , 2007 .

[31]  K. A. Ericsson,et al.  Verbal reports as data. , 1980 .

[32]  Lotfi A. Zadeh,et al.  PRUF—a meaning representation language for natural languages , 1978 .

[33]  T. L. Saaty.  A Scaling Method for Priorities in Hierarchical Structures , 1977 .

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

[35]  Benjamin Kuipers,et al.  Computer power and human reason , 1976, SGAR.

[36]  T. Saaty.  Measuring the Fuzziness of Sets , 1974 .

[37]  Albert N. Badre,et al.  On the Precision of Adjectives Which Denote Fuzzy Sets , 1974 .

[38]  J. Parry.  The psychology of human communication , 1967 .