Evaluating Incomplete DCOP Algorithms On Large-Scale Problems

摘要: The distributed constraint optimization problem (DCOP) has emerged as one of the most promising coordination techniques in multi-agent systems (MAS). However, because DCOP is known to be NP-hard, existing are often unsuitable for large-scale applications, which require scalable algorithms deal with severely limited computing and communication. Moreover, selection algorithm a challenging critical task obtaining desirable performance on certain MAS domains. In this paper, we present analysis incomplete DCOPs. We experimentally evaluate state-of-the-art two types problems involving hundreds variables different network topologies densities. Such can help mitigate challenges number realistic large-scale, complex applications.