Informationsdienste und elektronische Märkte
Prof. Dr. Andreas Geyer-Schulz | Schroff-Stiftungslehrstuhl

Institut für Wirtschaftsinformatik und Marketing
Fakultät für Wirtschaftswissenschaften

Informationsdienste und elektronische Märkte > Studium

Teilnehmen

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Inhalt

Details about the lecture and tutorial:

• All live sessions are held via Zoom and announced through Ilias. Details of the Zoom meeting will be announced in the Ilias course.
• The lectures are recorded on video and made available on Ilias. We offer regular live question and answer sessions on the contents of the last weeks. These sessions take place during regular lecture hours (Thursday, 10:00 am).
• The tutorials are held as live sessions. All tutorials take place at the regular dates (Thursday, 12:00 pm - 1:30 pm) on a roughly bi-weekly schedule. The first tutorial is on April 22.

All lecture and tutorial material, as well as the latest annoucements, can be found in Ilias. Further literature is references on this website.

Course Description

The key assumption of this lecture is that the concept of artificial intelligence is inseparably linked to the economic concept of rationality of agents. We consider different classes of decision problems - decisions under certainty, risk and uncertainty - from an economic, managerial and AI-engineering perspective:

From an economic point of view, we analyze how to act rationally in these situations based on classic utility theory. In this regard, the course also introduces the relevant parts of decision theory for dealing with multiple conflicting objectives, incomplete, risky and uncertain information about the world, assessing utility functions, and quantifying the value of information ...

From an engineering perspective, we discuss how to develop practical solutions for these decision problems, using appropriate AI components. We introduce a general, agent-based design framework for AI systems, as well as AI methods from the fields of search (for decisions under certainty), inference (for decions under risk) and learning (for decisions under uncertainty).

Where applicable, the course highlights the theoretical ties of these methods with decision theory.

We may also discuss ethical and philosophical issues concerning the development and use of AI.