Expert Systems

The course provides an overview of topics in the field of Expert Systems. The course also provides the student with a working knowledge of designing an expert system and applying expert system technology in designing and analyzing knowledge engineering systems. The first part of the course covers historical background, knowledge acquisition and knowledge representation including propositional calculus, predicate calculus, semantic networks, frame systems and production rules. Various search techniques will be discussed. Fuzzy logic systems, neural network systems and computer vision systems will be briefly discussed in the second part of the course. Languages for AI problem solving such as Prolog and/or LISP will be used. The third part of this course will be devoted to the design of expert systems. Applications of expert systems in engineering system design and analysis will be stressed throughout. Case studies will be discussed. Class project is required. Students are encouraged to design expert systems for his/her own engineering applications, and an expert shell will be used to implement the design.