Exploring self organized emergence in an agent-based synthetic warfare lab

Artificial-life techniques - specifically, agent-based models and evolutionary Learning algorithms - provide a potentially powerful new approach to understanding some of the fundamental processes of war. This paper introduces a simple artificial-like "toy model" of combat called Enhanced ISAAC Neural Simulation Tool (EINSTein). EINSTein is designed to illustrate how certain aspects of land combat can be viewed as self-organized, emergent phenomena resulting from the dynamical web of interactions among notional combatants. EINSTein's bottom-up, synthesist approach to the modeling of combat stands in stark contrast to the more traditional top-down, or reductionist approach taken by conventional military models, and represents a step toward developing a complex systems theoretic toolbox for identifying, exploring, and possibly exploiting self-organized emergent collective patterns of behavior on the real battlefield. A description of the model is provided, along with examples of emergent agent patterns and behaviors.