3rd Place at ACM SIGSPATIAL GisCup 2019

Optimizing the Spatio-Temporal Resource Search Problem With Reinforcement Learning

Felix Borutta, Sebastian Schmoll and Sabrina Friedl won the 3rd Place at ACM SIGSPATIAL GisCup 2019 for their contribution "Optimizing the Spatio-Temporal Resource Search Problem with Reinforcement Learning".

Congrats from us!

Learn more

#award #research #seidl

Subscribe to RSS News feed

28.04.2026

Björn Ommer: How AI Can Transform Society if We Use It Responsibly

MCML PI Björn Ommer explains the philosophy behind Stable Diffusion and why his team focuses on efficiency.

23.04.2026

When Vision AI Hallucinates Details

Why do vision-language models invent details? Our PI Zeynep Akata and her team present a fix for AI hallucinations at CVPR 2026.

22.04.2026

MCML at ICLR 2026

MCML researchers are represented with 36 papers at ICLR 2026 (33 Main, and 3 Workshops).

20.04.2026

Research Highlights from Germany’s AI Competence Centers

Several research projects associated with MCML are highlighted in the “Successes of German AI Research” overview.

16.04.2026

Welcoming Achim Lilienthal to MCML

Achim J. Lilienthal joins MCML as PI, focusing on perception systems, robotics, and AI in dynamic environments.

3rd Place at ACM SIGSPATIAL GisCup 2019

Optimizing the Spatio-Temporal Resource Search Problem With Reinforcement Learning

Related