Agents, infrastructures and policy

Current challenges, such as climate change or military conflicts, highlight the great importance of urban supply infrastructures. Such infrastructures are built to serve human needs and are simultaneously influenced by the behavior of the humans they serve. Due to these interdependencies of human (social) and technical systems, infrastructure systems are often regarded as “socio-technical systems”.

One paradigm to model socio-technical systems is agent-based modeling. This approach represents the behavior of many individual actors (called agents) in a system and is used to simulate the behavior of the whole system.

This approach of agent-based modeling is used by researchers of the FST research group on Urbanization and Infrastructure . The FST research group investigates infrastructures in the context of crises and the infrastructures resilience to such crises. This research group cooperated with the Institute for the Protection of Terrestrial Infrastructures at the German Aerospace Center (DLR) and the LOEWE Center emergenCITY.

Resulting from this cooperation, a new paper entitled “Modeling and Validation of Residential Water Demand in Agent-Based Models: A Systematic Literature Review” was published in the Special issue “Review Papers of Urban Water Management” of the journal Water by MDPI. The paper investigates (i) how agent-based models of residential water demand should be validated, (ii) how such models are commonly built and (iii) validated, and (iv) how these validation practices compare to the recommendations drawn from question (i).

The results of this literature review indicate, that highly realistic models (i.e., highly detailed models representing specific real-world systems) for the planning, management, and policy of urban water resources are the most prominent applications for agent-based models of residential water demand. While some models are thoroughly validated, quantified validation on test data distinct from calibration data should be emphasized and used to communicate the confidence in results and recommendations drawn from the models. Pattern-oriented validation, validation on multiple levels and on higher moments of aggregated statistics should be considered more often. These findings expand prior literature by providing a more extensive sample of reviewed articles and recommending specific approaches for the validation of models.

The paper can be accessed openly at https://doi.org/10.3390/w15030579.