Name
Abstract | ||
|---|---|---|
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 algorithm. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2739482.2764643 | GECCO (Companion) |
Field | DocType | Citations |
Mathematical optimization,Evolutionary algorithm,Computer science,Potential field,Genetic algorithm,Offensive | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jonas Schmitt | 1 | 0 | 1.01 |
| Sabine Seufert | 2 | 0 | 0.34 |
| Christian Zoubek | 3 | 0 | 0.34 |
| Harald Köstler | 4 | 197 | 25.94 |