  This paper uses neuroevolution of augmenting topologies to evolve control
tactics for groups of units in real-time strategy games. In such games, players
build economies to generate armies composed of multiple types of units with
different attack and movement characteristics to combat each other. This paper
evolves neural networks to control movement and attack commands, also called
micro, for a group of ranged units skirmishing with a group of melee units. Our
results show that neuroevolution of augmenting topologies can effectively
generate neural networks capable of good micro for our ranged units against a
group of hand-coded melee units. The evolved neural networks lead to kiting
behavior for the ranged units which is a common tactic used by professional
players in ranged versus melee skirmishes in popular real-time strategy games
like Starcraft. The evolved neural networks also generalized well to other
starting positions and numbers of units. We believe these results indicate the
potential of neuroevolution for generating effective micro in real-time
strategy games.
