In my research, I’m concernced with increasing the robustness of autonomous systems against external disturbances of physical nature, therefore hardware-related disturbances that are not caused by software. Concrete aspects are 1) detection, assessment and - if possible - automated prediction of component breakdowns within the scope of an autonomous system, 2) compensation through redundancy or configuration adaption as well as 3) delegation of maintenance activities involving external agents, such as human repair workers.

Relevant fields of research as well as other interests of mine are:

• Reinforcement Learning
• Evolutionary Machine Learning
• Predictive Maintenance
• Computational Self-Awareness

• Dealing with Hardware-related Disturbances in Organic Computing Systems. Markus Görlich-Bucher. In: INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft (Workshop-Beiträge), Draude, C., Lange, M. & Sick, B. (Eds.). Gesellschaft für Informatik e.V., Bonn, Germany, pp. 517–529.
• Towards Physical Disturbance Robustness in Organic Computing Systems using MOMDPs. Markus Görlich, Anthony Stein, Jörg Hähner. In: Workshop Proceedings of the 32nd International Conference on Architecture of Computing Systems, ARCS 2019, 20–23 May 2019, Copenhagen, Denmark, pp. 135–142.
• Predictive Maintenance in Complex Systems. Markus Görlich. 2019. In: Organic Computing: Doctoral Dissertation Colloqium 2018, Tomforde S., Sick B. (Eds.). Kassel University Press, Kassel, Germany.