Knowledge verification for fuzzy expert systems

Abstract The introduction and use of fuzzy logic has strengthened knowledge representation and reasoning capability in expert systems; nevertheless, it also increases the complexity and difficulty of knowledge verification, which is known to be an important issue for building reliable and high performance expert systems. In the past decade, knowledge verification problems, e.g., redundancy, conflict, circularity and incompleteness of knowledge, have been widely discussed from the viewpoint of using binary logic; nevertheless, the issue of verifying fuzzy knowledge is seldom discussed. In this paper, we attempt to detect potential structural errors among fuzzy rules by proposing a fuzzy verification algorithm. Moreover, a system for verifying fuzzy knowledge base has been developed based on the novel approach.

[1]  Jin-Fu Chang,et al.  Knowledge Representation Using Fuzzy Petri Nets , 1990, IEEE Trans. Knowl. Data Eng..

[2]  Chih-Hung Wu,et al.  A token-flow paradigm for verification of rule-based expert systems , 2000, IEEE Trans. Syst. Man Cybern. Part B.

[3]  Shian-Shyong Tseng,et al.  Building a CAL Expert System based upon Two-phase Knowledge Acquisition , 2002, Expert Syst. Appl..

[4]  John Durkin,et al.  Expert systems - design and development , 1994 .

[5]  Eugene Santos Verification and validation of Bayesian knowledge-bases , 2001, Data Knowl. Eng..

[6]  Dan C. Marinescu,et al.  Logical Inference of Horn Clauses in Petri Net Models , 1993, IEEE Trans. Knowl. Data Eng..

[7]  Derek L. Nazareth,et al.  Verification of rule-based knowledge using directed graphs , 1991 .

[8]  Du Zhang,et al.  PREPARE: A Toll for Knowledge Base Verification , 1994, IEEE Trans. Knowl. Data Eng..

[9]  Chih-Hung Wu,et al.  Enhanced high-level Petri nets with multiple colors for knowledge verification/validation of rule-based expert systems , 1997, IEEE Trans. Syst. Man Cybern. Part B.

[10]  Walter Kintsch,et al.  11 – Models for Free Recall and Recognition1 , 1970 .

[11]  Victor R. L. Shen,et al.  Verification of Knowledge-Based Systems Using Predicate/Transition Nets , 2008, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[12]  Gary Riley,et al.  Expert Systems: Principles and Programming , 2004 .

[13]  Derek L. Nazareth,et al.  Investigating the Applicability of Petri Nets for Rule-Based System Verification , 1993, IEEE Trans. Knowl. Data Eng..

[14]  Bart Kosko,et al.  Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence , 1991 .

[15]  Edward H. Shortliffe,et al.  An Approach to Verifying Completeness and Consistency in a Rule-Based Expert System , 1982, AI Mag..

[16]  Puyin Liu,et al.  Mamdani fuzzy system: universal approximator to a class of random processes , 2002, IEEE Trans. Fuzzy Syst..

[17]  SarkarSumit,et al.  Using Directed Hypergraphs to Verify Rule-Based Expert Systems , 1997 .

[18]  Ke Zeng,et al.  A comparative study on sufficient conditions for Takagi-Sugeno fuzzy systems as universal approximators , 2000, IEEE Trans. Fuzzy Syst..

[19]  Mohan Tanniru,et al.  A Petri-Net Based Approach for Verifying the Integrity of Production Systems , 1992, Int. J. Man Mach. Stud..

[20]  Robert M. Gagné,et al.  The Conditions of Learning and Theory of Instruction , 1985 .

[21]  Robert Glaser,et al.  Thoughts on Expertise , 1985 .

[22]  Jeffrey J. P. Tsai,et al.  Fuzzy Rule Base Systems Verification Using High-Level Petri Nets , 2003, IEEE Trans. Knowl. Data Eng..

[23]  Michael C. McFarland,et al.  Formal verification of sequential hardware: a tutorial , 1993, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[24]  J. Deese The structure of associations in language and thought , 1966 .

[25]  Senén Barro,et al.  Fuzzy reasoning supported by Petri nets , 1994, IEEE Trans. Fuzzy Syst..

[26]  Jonathan Lee,et al.  A high-level Petri nets-based approach to verifying task structures , 2002 .

[27]  Shian-Shyong Tseng,et al.  A new architecture of object-oriented rule base management system , 1999, Proceedings Technology of Object-Oriented Languages and Systems (Cat. No.PR00393).

[28]  Bart Kosko,et al.  Neural networks and fuzzy systems , 1998 .

[29]  Gabriel Valiente,et al.  Verification of knowledge base redundancy and subsumption using graph transformations , 1993 .

[30]  Mysore Ramaswamy,et al.  Using Directed Hypergraphs to Verity Rule-Based Expert Systems , 1997, IEEE Trans. Knowl. Data Eng..

[31]  S. S. Tseng,et al.  EMCUD: A Knowledge Acquisition Method which Captures Embedded Meanings Under Uncertainty , 1990, Int. J. Man Mach. Stud..