We attack the problem of evolving high performance micro behaviors in 3D RTS- game-like simulations. Prior work had shown the potential for the Meta-Search approach to evolve high performance micro for RTS games like StarCraft. We extend this work by moving to 3D and by moving to more realistic physics for simulating the movement of entities in our RTSgame- like simulation.We compare the evolved micro performance of our entities with different physics models of motion on the same scenarios against identical opponent units in a 3D RTS simulation. Results show that our genetic algorithm approach works to reliably evolve high quality 3D micro behaviors for entities independent of the physics model used. Furthermore, experiments show that the entity's acceleration has more of an effect on performance than rotation speed. Our work provides evidence for the generalizability of an evolutionary approach to generating complex behavior for 3D RTS games, training simulations, and real-world unmanned vehicles.
