Inhalte

To facilitate the adoption of real-world fleet management apps such as the ride-pooling BVG Muva app and the drone-monitoring POIApp, we propose to integrate virtual assistants that can generate explanations and, thus, respectively support commuters in their daily trip planning and farmers in their daily agriculture irrigation. The course focuses, therefore, on 'How can we generate explanations for ride pooling and drone monitoring?'. To answer this question, the X-Student Research Group will receive the opportunity to develop new methods for generating explanations by combining ideas from computer science, economy, social science, and computational social choice. Prerequisites are skills in mathematics, programming (e.g. Python, Java, C++), statistics (e.g. mean, standard deviation), or ethics. Activities include developing ideas, individual supervision, team tasks, invited talks, and conference participation. Successful completion requires that students present their results and submit reports with these results at the end of the semester.

Kontakt

aleksandrov.d.martin@gmail.com

Link zum Vorlesungsverzeichnis

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