Logic, Language and Learning

Spezialvorlesung

Logic, Language and Learning

Prof. Dr. Luc De Raedt

• Lectures:
• Tuesday 14-16 01-009/13 101
• Thursday 9-10 01-009/13 101

• Exercises:
• Thursday 10-11 01-009/13 101

• Credit points (Kreditpunkte):
• 6

• Language:
• English

• Overview:

This course will deal with Computational Logic, Natural Language Processing, Machine Learning, and theintersections of these three areas. The first part of the course will be devoted to Prolog, probably the most popular language for programming artificial intelligence applications. Prolog is based on first order logic. Hence, programming simply takes the form of declaring axioms in first order logic. Executing Prolog programs is then based on the orem proving. The course will introduce the basic concepts of logic programming and Prolog, and present example programs from Machine Learning and Natural Language Processing. The Prolog part of the course will largely be based on the book "Simply Logical" by Peter Flach, Wiley, 1994. The second part of the course will introduce Inductive Logic Programming (ILP), the study of Machine Learning and Data Mining within representations offered by logic programming and Prolog. In this part, we will use our own slides, but useful material on the topic can be found in the book "Relational Data Mining" edited by Saso Dzeroski and Nada Lavrac, Springer, 2001. The third part of the course will present Natural Language Processing in logic programming representations (as introduced in the first part) and ILP applications to Natural Language Processing. An introduction to Natural Language Processing (NLP) is given in "Natural Language Understanding" by James Allen, Addison-Wesley, 2nd Edition, 1995.

• Additional information about the course::
• The final exam is scheduled for September 6th, 10-12, lecture hall in building 082. In case of questions, send email to Prof. De Raedt
• During the course, you will find up to date information here, as well as on the specific slides and exercise web page