Learning fuzzy rules with tabu search-an application to control

We present an approach for the automatic definition of the fuzzy rules for a fuzzy controller based on the use of the tabu search (TS) scheme. We show also how the application of the TS process to the learning of a fuzzy rule base can be improved using heuristic symbolic meta rules. The paper is divided in two parts. The first part presents an introduction to TS and different learning schemes which can be used to apply it for the determination of the fuzzy control rules. The second part illustrates the application of the proposed techniques to a specific control problem-the parking of a truck and trailer. In particular, Section V illustrates the definition of a rule base for a static fuzzy controller, while Section VI presents the construction of an adaptive parking controller     

Development and application of expert systems in audit services

The authors evaluate research and development in the design of expert systems for the audit domain, providing an overview of the domain of expert judgment involved in the audit process. A framework used to present and analyze work to date and to guide future efforts is constructed. Methods of knowledge acquisition being used to develop audit applications are examined. The authors address knowledge representation for the audit domain. Most systems developed for auditing are rule-based systems. Currently, however, other representational forms are being tested that may be more appropriate for dealing with audit complexity. Progress being made in expert system validation is considered, and the current state of development and directions for future efforts are briefly discussed