|Title||Multi-Agent Coordination: DCOPs and Beyond|
|Publication Type||Conference Paper|
|Year of Publication||2011|
|Editor||Walsh NICTAToby, NSW Uof|
|Conference Name||Twenty-Second International Joint Conference on Artificial Intelligence|
Distributed constraint optimization problems (DCOPs) are a model for representing multi-agent systems in which agents cooperate to optimize a global objective. The DCOP model has two main advantages: it can represent a wide range of problem domains, and it supports the development of generic algorithms to solve them. Firstly, this paper presents some advances in both complete and approximate DCOP algorithms. Secondly, it explains that the DCOP model makes a number of unrealistic assumptions that severely limit its range of application. Finally, it points out hints on how to tackle such limitations.
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