Nach positiver Absolvierung der Lehrveranstaltung sind Studierende in der Lage...
After successful completion of the course, students are able to critically read and evaluate scientific articles. They are able to work independently to gain an understanding of recently published results, and the methods and proofs behind them. They can communicate the central ideas of their selected topics to non-experts and discuss the value of the presented findings. They know the key features of good oral presentations and the preparation of a corresponding seminar paper. Moreover, they will understand the relevant results of the topics of fellow students.
Participants of the seminar work on selected topics from a relevant subfield of Artificial Intelligence: decision making and computation.
Decision making problems arise from a diverse range of research areas such as social choice theory, game theory, political sciences, computer sciences, and multi-agent systems. Typical problems include how to aggregate individual preferences or judgments to reach a consensus, how to fairly allocate a set of resources to some agents, how to optimally assign schools or colleges to students based on their preferences, or how to recommend potential interesting products such as movies to a user based on her and others’ past and current preferences. During the seminar we explore relevant topics in decision making, and discuss mathematical and axiomatic properties as well as algorithmic and complexity issues of societal decision making problems.
Potential topics include:
- preference aggregation and (multi-winner) voting rules,
- restricted preference domains and their applications,
- matching under preferences,
- strategies and equilibria in game theory,
- cake cutting protocols,
- fair allocation of resources,
- judgment aggregation,
- simple games, and
- the measurement of political power.