Course ObjectiveThis course gives an overview over the theory and practice of
Intelligent Systems, systems that perceive, reason, learn, and act
Students will acquire practical skills in developing intelligent systems
building on a thorough understanding of well-understood Artificial
Intelligence approaches, including Knowledge Representation and Machine
Course ContentThe course will provide an in-depth understanding of classical AI
problems and approaches, such as search, knowledge representation,
machine learning, etc., by deepening the theoretical understanding and
ability to apply those techniques in practice.
Teaching MethodsThe course will be centered on the practical task of designing
intelligent agents that perform in a challenging competition against
There will be 12 lectures in the first 3 weeks, as well as a number of
practical sessions in a lab, working groups to help with the course
material and a significant amount of self-study, both to
familiarise oneself with the AI theory and methods, and to program an
Intelligent System using those methods.
Method of AssessmentThere will be an exam (probably digital) and a groups assignment.
LiteratureRussell, Norvig: Artificial Intelligence: A Modern Approach. Most recent
Edition. Recommended, but not compulsory. There will be a reader.
Target Audience2CS, 2LI, 2IMM
|Language of Tuition||English|
|Faculty||Faculty of Science|
|Course Coordinator||dr. K.S. Schlobach|
|Examiner||dr. K.S. Schlobach|
dr. K.S. Schlobach
You need to register for this course yourself
Last-minute registration is available for this course.
|Teaching Methods||Seminar, Lecture, Practical|
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