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Green (International Journal of Forecasting, 18, 321–344) considers one method of testing the predictive value of game theory for conflict situations, and finds that role-playing does better. I discuss a second method, one that combines game theory and role-playing. This method has already been used with success to solve practical business problems. I argue game theory will have to play a critical part if role-playing is to be reliable for forecasting conflict outcomes. Existing research that combines game theory and experimental economics holds important lessons for the design of role-playing exercises.

If I needed advice on building a rocket, I wouldn’t ask a physicist. I would ask an engineer. Physics is critical to a successful launch. But to build a rocket, you also need to know something about material science, chemistry, and so on. It is the engineer who synthesizes the necessary knowledge for practical use. In the same way, if I wanted to forecast a real-world conflict, I wouldn’t ask the advice of a game theorist. Strategic behavior, the object of game theory, is surely important, but so too psychology, institutional factors, and so on. But then, for conflict situations, who is the equivalent of the engineer? One answer would be domain experts; we might, for instance, forecast political conflicts using politicians. The Green (2002) study suggests an intriguing alternative, another way of combining the knowledge necessary to obtain a forecast: role-playing. Unlike myself (a game theorist and an experimental economist), Green conceives of role-playing and game theory as competing methods: Role-playing and game theory depend on contrasting assumptions about modeling conflict situations. Those who adopt a game theoretic approach must assume that the complexity of a conflict can be radically reduced without losing predictive validity. The role-play approach, on the other hand, incorporates complexity and emotion into a simulation (Table 1 and Fig. 1). In contrast, I will argue that role-playing will need game theory if it is to be successful at practical forecasting. Role-playing in the guise of experimental economics—and guided by game theory—is already being used to solve real world business problems. These problems are related to the kind of conflict situations Green studies, but also different. That said, research in experimental economics, guided by game theory, presently has some important lessons for role-playing design.

To date, most work combining role-playing experiments and game theory, and dealing with conflict situations, focuses on substantial simplifications of real world conflict situations. But contrary to Green (2002), I would say that this is the strength of the work, not its weakness: Some of the key principles in launching a rocket were gleaned from studying the free fall of an apple. Simplification allows us a clearer view of the fundamental mechanisms at work. That said, it’s important to keep our eyes on what practical import we can expect from the work. Clearly, the insights from game theory will need to be combined with knowledge from other fields (e.g. domain specific knowledge such as law) if role-playing is to be used to forecast real world outcomes. Green’s results suggest that role-playing may be an appropriate vehicle for doing the combining. Game theory and role-playing could prove a valuable partnership.