Search-based software test data generation: a survey: Research Articles
Software Testing, Verification & Reliability
Cooperative Multi-Agent Learning: The State of the Art
Autonomous Agents and Multi-Agent Systems
Using genetic algorithms for early schedulability analysis and stress testing in real-time systems
Genetic Programming and Evolvable Machines
Testing the limits of emergent behavior in MAS using learning of cooperative behavior
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
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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.