Improving testing of multi-unit computer players for unwanted behavior using coordination macros

We present an improvement to behavior testing of computer players based on evolutionary learning of cooperative behavior that extends the known approach to allow for so-called coordination macros. These macros represent knowledge about the application and are interpreted by the agents that are testing the computer player based on the current situation to achieve coordination between the agents. Our experimental evaluation using this approach to test computer players for one competition scenario of the ORTS real-time strategy game showed that the macros enabled the testing system to find weaknesses much faster than the previous approach, respectively to find weaknesses that the previous approach was not able to find within the given resource limit.