Self-Organizing Multi-Agent Systems

In this thesis I research the ability of groups of agents to organize their collective behavior, without any human intervention. Using a framework for gathering information of the behavior, analyzing the performance, and updating the behavior, the agents can adapt to changing environments or user requirements. In my thesis I use different mechanisms driving the self-organization, but mostly focus on Distributed Constraint Optimization Problems (DCOPs) to do so. A new algorithm called CoCoA (Cooperative Constraint Approximation) is used to quickly find solutions that are near-optimal. Throughout my thesis the approach is put to use for different applications such as sensor networks, wireless power transfer networks and smart grids.