Potential-Field-Based Unit Behavior Optimization for Balancing in StarCraft II - Schmitt, Jonas; Seufert, Sabine; Zoubek, Christian; Köstler, Harald (GECCO Companion '15 Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, 2015)
This article presents an evolutionary algorithm for optimizing the offensive behavior of opposing units in the real-time strategy game StarCraft II. Encounters between different unit groups are examined and described. The goal for each group is to deal maximal damage to the opposing group while receiving a minimal amount of damage at the same time. The actions each unit performs are determined by accumulating a number of predefined potential fields. Dependent on the statistics of the involved units, the parameters of these fields then fully describe the behavior of each individual unit. Since this includes a huge number of possibilities, the set of optimal parameter values for both groups in an encounter is obtained by applying an evolutionary algorith
UnivIS-Import:2016-02-10:Pub.2015.tech.IMMD.lsinfs.potent