Learning of cooperative behavior for multi-agent software testing
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AbstractIn this thesis work we present a new model for testing complex systems. Our model is based upon using learning of cooperative behavior for testing complex systems. Specifically, we concentrate on the testing of multi-agent systems for high level behavior. Our model includes a multi-agent system that learns the required coordination needed between a group of tester agents to cause a desired behavior to be exhibited in the targeted system. As a test application, we use the Agent Rescue Emergency Simulator (ARES) system. The ARES system presents a simple post urban disaster zone where different agents must work together to save survivors . The ARES system is used to show our model in action as it relates to the testing problems presented by the system.
Bibliography: p. 100-104