The course introduces the principles of logic-based knowledge representation and reasoning, as well as other important symbolic approaches to representing and reasoning about knowledge such as production systems, frames, taxonomies and Kripke models. How to represent different sorts of knowledge, such as uncertain or incomplete knowledge, knowledge about action and change, and knowledge about default situations, is discussed. Various types of reasoning are discussed, such as logical entailment, explanation and planning.

• demonstrate command of theoretical knowledge about principles for logic-based representation and reasoning.
• demonstrate a basic understanding of production systems, frames, inheritance systems and approaches to handling uncertain or incomplete knowledge.
• demonstrate a basic understanding of principles for reasoning with respect to explanation and planning.
• analyze and design knowledge based systems intended for computer implementation.
• demonstrate a broad understanding of how knowledge based systems work which provides a solid foundation for further studies and for assessing when knowledge based approaches to problem solving are appropriate.

Lectures, seminars and data labs, normally 2 + 2 hours per week for 12-15 weeks.