Evolving team tactics using potential fields

This paper investigates the evolution of group tactics and counter tactics for wargaming and real-time strategy games. Inspired by potential field methods in robotics, we compactly represent group behavior as a combination of several potential fields and evolve potential field parameters against hand-coded opponent groups. A novel real-coded evolutionary algorithm encourages tactic diversity by using a new diversity metric to mediate parent selection for recombination. Preliminary results indicate that we can quickly evolve counter tactics that beat hard coded opponent groups.