Aggregation Disaggregation And The 3 1 Rule In Ground Combat

Aggregation, Disaggregation, and the 3:1 Rule in Ground Combat

Validity of Aggregation. In this report I illustrate some generic subtleties of aggregation and disaggregation in combat models by starting with an analytically tractable model at one level of detail and then attempting to derive an aggregate model. In particular, suppose that a Lanchester square law is valid for ground combat in each of a number of individual sectors. What equations then describe events at a higher, more aggregate, level? What factors determine whether a closed aggregate-level model exists (i.e., a reasonably accurate model dependent only on aggregate-level variables and with any coefficients being independent of time)? The answer is that what matters is "outside" the "detailed model" altogether, notably (1) higher-level strategy, (2) command and control, and (3) the relative durations of several time scales for battle and maneuver. These factors have major effects on whether a valid aggregate-level model exists and, if it does, what values its coefficients should have. The 3:1 Rule. A bonus of this analysis is a clarification of when the famous 3:1 rule applies. If it applies at the sector level, then it may or may not apply at a more aggregate level. Indeed, in a theater with multiple corps sectors (e.g., the old Central Region of Europe), the theater-level break-even ratio will typically be more like 1.5:1 than 3:1. By contrast, it is possible for the same 3:1 rule to apply at several lower levels (e.g., corps, division, brigade, and even battalion). In mobile combat in which there is no particular defense advantage, the theater-level break-even force ratio may be about 0.8 or 0.9.

Distributed Interactive Simulation of Combat

Artificial War: Multiagent-based Simulation Of Combat

Military conflicts, particularly land combat, possess the characteristics of complex adaptive systems: combat forces are composed of a large number of nonlinearly interacting parts and are organized in a dynamic command-and-control network; local action, which often appears disordered, self-organizes into long-range order; military conflicts, by their nature, proceed far from equilibrium; military forces adapt to a changing combat environment; and there is no master “voice” that dictates the actions of every soldier (i.e., battlefield action is decentralized). Nonetheless, most modern “state of the art” military simulations ignore the self-organizing properties of combat.This book summarizes the results of a multiyear research effort aimed at exploring the applicability of complex adaptive systems theory to the study of warfare, and introduces a sophisticated multiagent-based simulation of combat called EINSTein. EINSTein, whose bottom-up, generative approach to modeling combat stands in stark contrast to the top-down or reductionist philosophy that still underlies most conventional military models, is designed to illustrate how many aspects of land combat may be understood as self-organized, emergent phenomena. Used worldwide by the military operations research community, EINSTein has pioneered the simulation of combat on a small to medium scale by using autonomous agents to model individual behaviors and personalities rather than hardware.