Explainable Fleet Management
Martin Aleksandrov
Hinweise für Studierende
Informationen zur Anmeldung zu X-Student Research Groups finden Sie auf der Website der Berlin University Alliance.
Die Teilnahme an einer X-Student Research Group ist anrechenbar im überfachlichen Wahlpflichtbereich (üWP) / im freien Wahlbereich/ im Wahlpflichtbereich/ im Studienbereich Allgemeine Berufsvorbereitung (ABV). Darüber hinaus besteht auf individuellen Antrag die Möglichkeit einer Anrechnung für andere Strukturbereichen in Bachelor- und Masterstudiengängen.
Modulbeschreibung: https://www.berlin-university-alliance.de/commitments/teaching-learning/sturop/research-groups/information/Modulbeschreibung_StuROPx_X-SRG_6LP.pdf
SchließenKommentar
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.
Institutional affiliation: Fachbereich Mathematik und Informatik, Institut für Informatik
Contact: aleksandrov.d.martin@gmail.com
online meeting information:
https://us05web.zoom.us/j/87347503540?pwd=X4Xgu97rC9kYu8L1PoKvsYmcWlEUw4.1
Meeting ID: 873 4750 3540
Passcode: 2q0bb1
16 Termine
Regelmäßige Termine der Lehrveranstaltung