CAUSality in multi-agEnt Systems: learning and verification (CAUSES)
The CAUSES project will enable the design and implementation of reliable and explainable AI systems by developing computational techniques to learn, analyse, explain, and verify causal effects in multi-agent environments. These techniques can be used for traffic control and scheduling tasks. ProRail will provide data and guidance, and will be able to use the findings of this project in the form of a prototype decision support system.
Kristina Gogoladze, Francisco Simoes,
Dr. M. (Thijs) van Ommen, Prof. Dr. M.M. Dastani, Dr. N.A. Alechina, Dr. Brian Logan
Grant funding agency and (co-)funding non-academic partners