Logic for Artificial Intelligence introduces the students to the semantics of logics for knowledge representation and reasoning. Logics form the formal foundation of knowledge representation and reasoning, which is a fundamental topic in Artificial Intelligence. The semantics of logics enable us to evaluate the intended meaning of knowledge representation formalisms, and the correctness and completeness of reasoning processes. Assumptions play an important role in practical applications such as model-based diagnosis, legal argumentation, and so on. In this course it will be investigated which properties a knowledge representation formalism that uses assumptions should possess and what the intended meaning of an assumption should be. The emphasis will be on applications of classical logics and on non-monotonic logics. After completing this course student will be able to analyse important properties of practical formalisms for knowledge representations and reasoning. The student will be able to judge for several knowledge representation formalisms whether it is able to represent the intended meaning of the knowledge to be represented and whether the derived conclusions are correct and complete.
Knowledge of Propositional and Predicate Logic