Payoffs to Using Agent-Based Models of Combat

6 Payoffs to Using Agent-Based Models of Combat 

Most traditional models focus on looking for equilibrium solutions among some set of (pre-defined) aggregate variables. The LEs are effectively mean-field equations, in which certain variables (i.e. attrition rate) are assumed to represent an entire force, the equilibrium state is explicitly solved for and declared the battle outcome. In contrast, ABMs focus on understanding the kinds of emergent patterns that might arise while the overall system is out of (or far from) equilibrium. 

The payoff of an agent-based approach is a radically new way of looking at fundamental issues of land combat. Models such as these are emphatically not to be used for prediction rather they are best used to enhance understanding. Specifically, agent-based models of combat are designed to help military theorists... 

Users are also given an opportunity to construct a context for understanding their own conjectures about dynamical combat behavior. The agent-based simulation is therefore a medium in which questions and insights continually feed off of one another. 

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