Abstract: This paper describes a genetic algorithm (GA) tool added to the MANA agent-based model to assist with scenario development. Squads of agents are given chromosomes consisting of genes made up from various personality weightings in the MANA model; the emphasis is on evolving clever tactics and behaviour given the weapons and equipment squads already have. Concepts from evolutionary biology such as gene recombination and mutations are then applied to evolve fittest squads to optimally defeat an enemy in a given MANA scenario. We demonstrate the GA tool using two examples: a simple shooting battle between two massed forces, and a reconnaissance/counter-reconnaissance scenario in which a small Blue squad attempts to locate a high value target within enemy territory. Communications links in the MANA model are utilized for the information sharing, thus highlighting issues of network enabled operations. Generally, the genetic algorithm is seen to be a useful addition to the toolkit of military modelling techniques based on complexity theory.