| Publication Details | 
| Category | Text Publication | 
| Reference Category | Journals | 
| DOI | 10.1016/j.ecolmodel.2018.10.006 | 
| Document | author version | 
| Title (Primary) | From cases to general principles: A call for theory development through agent-based modeling | 
| Author | Lorscheid, I.; Berger, U.; Grimm, V.; Meyer, M. | 
| Source Titel | Ecological Modelling | 
| Year | 2019 | 
| Department | OESA | 
| Volume | 393 | 
| Page From | 153 | 
| Page To | 156 | 
| Language | englisch | 
| Keywords | Individual-based modeling; Theory development; Epistemological perspectives | 
| Abstract | Virtually all current major social and environmental challenges such as financial crises, migration, the erosion of democratic institutions, and the loss of biodiversity involve complex systems comprising decision-making, interacting, adaptive agents. To understand how such agent-based complex systems function and respond to change and disturbances, agent-based modeling (ABM) is increasingly recognized as the main way forward. Many motivating examples of agent-based models exist that are realistic enough to successfully support the management of complex systems, but these solutions are case-specific and contribute few general insights into the functioning of systems. General theory, though, is highly needed because we cannot model each system and question. Still, across disciplines, a critical mass of expertise has accumulated that could transform ABM into a more coherent and efficient approach to discover the functioning of complex social-economic-ecological systems. To this end, we need a cross-disciplinary discussion among researchers and a goal-oriented synthesis to identify the general principles and theories essential to improve our understanding and management of complex systems. | 
| Persistent UFZ Identifier | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=21539 | 
| Lorscheid, I., Berger, U., Grimm, V., Meyer, M. (2019): From cases to general principles: A call for theory development through agent-based modeling Ecol. Model. 393 , 153 - 156 10.1016/j.ecolmodel.2018.10.006 | |
