Aggregating Opinions to Optimize Multi-objective Urban Tactical Position Selection

In this research-in-progress paper we present a new real-world domain for studying the aggregation of different opinions: optimal urban tactical position selection (TPS). This is an important and foreseeable real world application, not only because cities have been viewed as centers of gravity by military planners throughout history, but also because the military significance of cities has increased proportionally as the global urbanization does. We first present a mapping between the domain of engineering research and that of the agent models present in the literature and use genetic multi-objective optimization method to generate Pareto TPS plans. Further we study the importance of forming diverse teams when aggregating opinions of different problem solvers for tactical position selection, and also the relationships of the number of problem solvers with time ratio and the solution efficiency. We show that a diverse team of problem solvers is able to provide better force deployment plans for early-stage decision makers to choose from. We also find that opinion aggregation methods, like approval voting, help to allocate a difficult problem solving among several computing resources, and at the same time ensuring the efficiency of solutions. Finally, we present next steps for a deeper exploration of our questions.