I am trying to build an evolution simulator in which there is group A and group B, each group has 9 members each generation. Each generation, each member of group A will enter a competition (in the form of combat) with a random member of group B, and fitness will be calculated based on how quickly and with how little losses will one member's army destroy the other. The best few members of each group then becomes the parents of the next generation.
(Note that an "individual" of each group is in fact a genetically determine neural network that controls a swarm of robots, think of it as a swarm of ants sharing the same DNA and thus can be effective consider one individual)
Will this end up with both group A and B having phenotype/strategy that do not change very much over many generations, or will it result in strategies that gradually changes throughout generation, with each successful, significant change out-smarting the opponent's old strategy until the opponent develop a counter strategy?