his course is about the logic of knowledge bases, in two distinct but related senses. On the one hand, a knowledge base is a collection of sentences in a representation language that entails a certain picture of the world represented. On the other hand, having a knowledge base entails being in a certain state of knowledge where a number of other epistemic properties hold. One of the principal aims of this course is to develop a detailed account of the relationship between symbolic representations of knowledge and abstract states of knowledge. Students wishing to attend the course should be familiar with first-order predicate logic.
The proseminar will be on different (sub-)topics from artificial intelligence. We largely follow the lines of the well known textbook by Stuart Russell and Peter Norvig “Artificial Intelligence - A Modern Approach”.
In this seminar we will study concepts of forgetting and relevance developed in the field of Knowledge Representation. Humans not only forget unintentionally but also intentionally, for example, when they obtain new information and delete previous contradicting and apparently false information. In fact, humans usually do not forget irrevocably; we can bring back memories and reconstruct forgotten knowledge. In formal languages as studied in KR, however, even supposedly simple forgetting often turns out very difficult. In this seminar, we will study techniques for forgetting in KR languages such as predicate logic, description logics, or answer set programs. Related to forgetting is the concept of relevance among different facts. For example, when some fact is to be forgotten, this may also affect other facts relevant to the forgotten fact. Relevance is useful to develop tractable reasoning and handling inconsistencies in a knowledge base.