The currently youngest subject area for Artificial Intelligence in Agricultural Engineering (KIA) complements the strong and wide-ranging expertise in the field of agricultural engineering of the institute of the same name with well-founded professional know-how in the research and application of Artificial Intelligence (AI) methods. It thus forms the interface between the agricultural science sector and computer science, more specifically the design and development of "intelligent" (information) technical systems.
The KIA conducts basic research on innovative AI methods. In particular, evolutionary methods of continuous machine learning (Evolutionary Intelligence). The focus is always on the applicability of the methodological repertoire to machines and systems that have to act robustly under real operating conditions. Established and novel principles of self-adaptive and self-organising distributed systems are considered and further developed for this purpose (Organic Computing). As an interface to agricultural engineering, interdisciplinary research with neighbouring (with regard to the Hohenheim CSH, but also cross-faculty) disciplines forms a further research strand of the KIA.
The overarching research vision will manifest itself in the future in holarchical, autonomously acting systems for agriculture, which make the challenges of "digital agriculture" (digital farming) and the inherent system complexity controllable through the use of AI and at the same time exploit the hidden potential.
