As a branch of artificial intelligence, commonsense reasoning, is concerned with the simulation of the human ability to handle problems in everyday life situations. These problems are characterized by ambiguity and uncertainty and typically require large amounts of background knowledge.
Humans naturally reason in the presence of incomplete and inconsistent knowledge, are able to reason in the presence of norms as well as conflicting norms and are able to quickly reconsider their conclusions when being confronted with additional information. The versatility of human reasoning illustrates that any attempt to model the way humans perform commonsense reasoning has to use a combination of many different techniques.
In this seminar we will discuss recent topics from the area of commonsense reasoning. We will become aquainted with different benchmarks in this area together with methods to tackle them.
The seminar is intended for master students in the area of Computer Science, Web Science, and related fields. The seminar will be held in English, and will consist of individual talks of students. Each student will research and prepare one topic in the area of commonsense reasoning, will give a presentation (30 minutes) about the topic, and will write a technical report (12 pages) about it. For the presentation as well as the preparation of the technical report it is recommended to follow the guidlines outlined in the document "Seminar Presentations and Technical Reports - Guidlines".
Knowledge in the area of commonsense reasoning or artificial intelligence is not mandatory to take part in the seminar. However it is assumed that all participant are familiar with the notion of propositional as well as predicate logic. To refresh your knowledge on logic, you could for example consider taking a look at . Students who are not sure if they meet this requirement can contact Claudia Schon.
Introductory meeting: February 8th 2018, 16:15 room B 017
Slides from the Introductory meeting
 Melvin Fitting: First-Order Logic and Automated Theorem Proving, Second Edition. Graduate Texts in Computer Science, Springer 1996, ISBN 978-1-4612-7515-2, pp. I-XVI, 1-326