Foundations of Artificial Intelligence (FAI) Group

Core Lecture: Artificial Intelligence

Organization. Successful participation in the course yields 9 ECTS.

The course consists of oral lectures, 2*90 minutes per week, as well as exercises that will be supervised in tutorial groups (90 minutes/week).

The lectures will be held Mondays 10:15--11:45 and Wednesdays 14:15--15:45, in HS002 (Building E1 3). There are four exceptions, i.e., dates where the lecture will be in Guenter-Hotz-Hoersaal (E2 2) instead: April 16, April 23, June 4, and June 18.

All lectures and tutorials will be held in English.

The lectures will be given by Prof. Joerg Hoffmann, and Prof. Wolfgang Wahlster for a block of 3 DFKI guest lectures. Prof. Slusallek and Dr. Kissmann will give further Guest Lectures.

The tutorials will be supervised by Dr. Peter Kissmann and Dr. Alvaro Torralba. The tutors are: Jeanette Aline Daum, Inken Hagestedt, Jesko Hecking-Harbusch, Sebastian Laska, Sreyasi Nag Chowdhury, and Frank Nedwed.

The lecture slides will be made available for download here, i.e., on this web page. By contrast, all exercises material and all interaction -- registration, announcements, technical discussions -- will be available and run through our Moodle pages. Apart from the lecture slide publication, this web page here will remain fixed throughout the course. (For the curious amongst you: the lecture slides will be made available here, as opposed to the Moodle pages, so that people from outside Saarland university can access them as well.)

To register for the course, open our Moodle pages, go to "Artificial Intelligence (Summer 2014)", and enter key "UDS-AI-14". You must have a valid email address ending with ".uni-saarland.de". (If you have no such email address, contact Peter Kissmann.)

For organizational details about the course, see Chapter 0 "About this Course" below.

Abstract. This course explores key concepts of Artificial Intelligence (AI), including heuristic search algorithms, adversarial search, constraint satisfaction problems, propositional and first-order reasoning, the automatic generation of heuristic functions in planning, and reasoning under uncertainty. We will highlight how these concepts are used in a variety of AI applications; in particular, guest lectures by researchers from DFKI are anticipated. Upon completion of the course, students should be able to write Bachelor and Master theses in AI. This core lecture is also the prerequisite for advanced courses such as Automatic Planning, Intelligent User Interfaces, and Semantic Web. Interested students will have the unique opportunity to participate in exciting AI research projects in the FAI group or at DFKI.

Exercises. The exercises will involve applying the introduced concepts and algorithms to examples, and leading simple proofs. Solutions can be submitted in groups of 3 authors, all of which must be registered into the same tutorial group.

Exam and final grade. There will be a written exam at the end of the course. 50 percent of the points from the exercises are needed for admission to the exam. The final grade will be determined based on the performance in the exam. A second, slightly harder, exam will be held end September/beginning October. The better grade of the two exams counts.

Course Material. There are two kinds of slides, pre-handouts and post-handouts. Pre-handouts do not contain the answers to questions asked during the lecture sessions, and do not contain the details for examples worked during the lecture sessions. The post-handouts do contain all this, and correct any bugs. The pre-handouts are made available one day before the lecture sessions on each chapter, the post-handouts are made available directly after the lecture sessions on a chapter are finished.

Most of the course follows the standard AI text book by Russel and Norvig (RN). HOWEVER, several chapters do NOT follow that book one-to-one, and some do not follow it at all. The ground truth throughout the course are the results as stated in the post-handouts. A few details about the relevant chapters of RN are given in the table at the end of this page, as well as at the end of each topic in the post-handouts.

Course Overview. The provisional outline of the course is specified in the following table: