Aim of the course
Expert systems are introduced as part of the research in the field of artificial intelligence (with usable functionality comparable to the role of domain experts). The lecture is aimed to deliver theoretical and practical knowledge which enables to design and build expert systems. This knowledge includes the basic ways of knowledge representation, inference algorithms and implementation of projects in the field of knowledge engineering.
Definition of expert systems, their tasks and the scope of usage. Functional model of architectures of expert based systems. Principles of knowledge representation in databases of domain knowledge bases and implementation of algorithms for inference engines. A general overview of the methods of knowledge representation including the language expression and scope of the tasks performed by the inference engines. Taking into account the methods of knowledge representation in probabilistic models of knowledge (basic - Naive Bayes and advanced - Bayes network). Rule-based knowledge representation and inference models, design options, including a variety of reasoning strategies. Non-probalistic methods of representation of uncertain knowledge and facts and algorithms for the propagation of uncertainty. Environment and tools for implementing expert systems. The basic elements of engineering knowledge and the process of creating expert systems with particular emphasis on knowledge acquisition and validation.
Overview of the course elements
Laboratory exercises of the design-implementation type allow to gain practical skills in the creation of knowledge bases using various forms of representation. Implementation of tasks enables comparison of not only different ways of knowledge representation, but also their actual usefulness in solving different types of expert tasks. Laboratory exercises allow to explore many original environments (e.g. shell) related to the implementation of expert systems.
1. S.Russell, P.Norvig, "Artificial Intelligence – A Modern Approach", Prentice Hall, New Jersey, 2003
2. J. Durkin, "Expert Systems - Design and Development", Prentice Hall, New Jersey, 1994
3. Z. Bubnicki, "Wstęp do systemów ekspertowych", PWN, Warszawa, 1990
4. J.J. Mulawka, "Systemy ekspertowe", WNT, Warszawa, 1996
5. J. Chromiec, E. Strzemieczna, "Sztuczna Inteligencja - Metody konstrukcji i analizy systemów eksperckich", Akademicka Oficyna Wydawnicza PLJ, Warszawa, 1995