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research tools & methods 7www.iiasa.ac.at summer 2018 ◼ options T he “fog of war” and Donald Rumsfeld’s “unknown unknowns” in Iraq in 2002, are quotes often used by military strategists and authors to convey the uncertainty surrounding military operations. It is perhaps understandable that those seeking to end conflict, or indeed pursue it, might turn to mathematical modeling for clarity. In the recent paper, “Conflicts among N armed groups: Scenarios from a new descriptive model,” Sergio Rinaldi and Fabio Della Rossa propose and analyze a model that describes armed conflict between a government group and one or two rebel groups. Rinaldi, a researcher at IIASA, says that a scarcity of reliable data has led to the belief that the outcome of such complex conflicts cannot be predicted. But what happens if the data is comprehensive and trustworthy? The model reveals that the dynamics among fighting groups can be extremely sensitive to the conflict’s initial conditions and parameter values. “This suggests that a conflict’s outcome may be practically unpredictable, even if very rich data sets were available,” says Rinaldi. He adds that this might be an uncomfortable truth for strategists who are increasingly turning to dynamic modeling to disperse some of that “fog of war.” “Rebels cannot be eradicated if they are highly fanatical” – Sergio Rinaldi For the modeled conflict, some interesting properties emerged. Government groups, if highly defensive, cannot go extinct, while their rebel opponents cannot be eradicated if they are highly fanatical. Instead, stalemates arise and when a conflict is caught in a turbulent stalemate, “the model allows one to determine when a short military intervention of an allied country should be performed to have the highest chances of eradicating the enemies,” conclude the researchers. Rinaldi and Della Rossa caution that their results are preliminary and that more subtle considerations–such as the existence of chaotic regimes and the systematic evaluation of the role of strategic factors like power, intelligence, and fanaticism–remain open and require further research. The many failed attempts to resolve drawn-out contemporary conflicts would seem to support their conclusions. KS Mathematical models and armed conflict–A case for caution Armed conflicts are widespread and yet their dynamics are poorly understood. A simple model can enable insights into the potential for stalemates and a conflict’s ultimate outcome. Further info Rinaldi S, Della Rossa F (2018). Conflicts among N armed groups: Scenarios from a new descriptive model. Nonlinear Dynamics 92: 3-12: [pure.iiasa.ac.at/14368] Sergio Rinaldi rinaldi@iiasa.ac.at Understanding terrorist organizations and responses In their paper “Differential Terror Queue Games”, IIASA researchers describe applying game-theoretic modeling to terrorist strategies and government responses. In these games, terrorists seek optimal attack rates, while the government simultaneously develops optimal counter- terror staffing levels. The researchers describe circumstances in which terror groups will either increase or decrease their attacks, for example, “they will attack less as they know that by planning terror plots they will strongly provoke counteractions.” The research aims to build on a growing body of academic literature on dealing with terrorism. Further info Wrzaczek S, Kaplan EH, Caulkins JP, Seidl A, & Feichtinger G (2017). Differential Terror Queue Games. Dynamic Games and Applications 7 (4): 578-593. [pure.iiasa.ac.at/13857] Gustav Feichtinger feichtin@iiasa.ac.at iiasa research