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Employing hypergraphs for efficient coalition formation with an application to electric vehicle cooperatives

Christianos Filippos

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Summary

This thesis proposes, for the first time in the literature, the use of hypergraphs for the efficient formation of effective agent coalitions. We put forward several formation methods that build on existing hypergraph pruning, transversal, clustering and hybrid algorithms, and exploit the hypergraph structure to identify agents with desirable characteristics. Our approach allows the near-instantaneous formation of high quality coalitions, adhering to multiple stated quality requirements. Moreover, our methods are shown to scale to dozens of thousands of agents within fractions of a second; with one of them scaling to even millions of agents within seconds. We apply our approach to the problem of forming coalitions to provide (electric) vehicle-to-grid (V2G) services. Ours is the first approach able to deal with large-scale, real-time coalition formation for the V2G problem, while taking multiple criteria into account for creating the electric vehicle coalitions. A sketch of these ideas appeared originally in a short paper in the 22nd European Conference on Artificial Intelligence (ECAI-2016). Afterwards, a full paper describing our work was published in the 14th European Conference on Multi-Agent Systems (EUMAS-2016).

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