Foundations of Artificial Intelligence (FAI) Group

Core Lecture: Artificial Intelligence

Organization. Lecturers: Prof. Joerg Hoffmann, and Prof. Wolfgang Wahlster.

The tutorials will be supervised by Dr. Alvaro Torralba. Tutors: TBA.

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). All lectures and tutorials will be held in English.

The lectures will normally be held Mondays 10:15--11:45 and Tuesdays 16:15--17:45, in Guenter-Hotz-Hoersaal (E2 2). There will be some exceptions, in day of the week, time, and/or place. Exact details are made available in the "Course Calendar" below.

Registration for the course/exams is in HISPOS as usual (contact Evelyn Kraska in case of questions). Registration for the tutorials is via our Moodle pages (next item). For details regarding tutorials registration (and other organizational aspects of the course), see the "About this Course" slide handouts (Chapter 0) below. If you have difficulties registering, or wish to change tutorials, please send an email Alvaro Torralba. Note that, for changing the tutorial group, you need a switching partner. You can try to find a switching partner via the "Technical Discussion" forum on the Moodle pages.

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 the FAI 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.)

Abstract. This course explores key concepts of Artificial Intelligence (AI), including formal knowledge representation, automated deduction, heuristic search algorithms, the automatic generation of heuristic functions in planning, reasoning under uncertainty, rule-based systems, and description logics. We will highlight how these concepts are used in several AI application-fields like spoken-dialog systems, expert systems, and intelligent network security. 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 at DFKI or in the FAI group.

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. For most lecture, there will be 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 Calendar. Lecture slots and contents are overviewed below.

ATTENTION: Lecture slots displayed in red in this table deviate from the regular lecture days/times.