Proceedings Abstracts of the Twenty-Third International Joint Conference on Artificial Intelligence

DeQED: An Efficient Divide-and-Coordinate Algorithm for DCOP / 566
Daisuke Hatano, Katsutoshi Hirayama

This paper presents a new DCOP algorithm calledDeQED (Decomposition with Quadratic Encoding to Decentralize). DeQED is based on the Divide-and-Coordinate (DaC) framework, where the agents repeatedly solve their updated local subproblems (the divide stage) and exchange coordination information that causes them to update their local sub-problems (the coordinate stage). Unlike other DaC-based DCOP algorithms, DeQED does not essentially increase the complexity of local subproblems and allows agents to avoid exchanging (primal) variable values in the coordinate stage. Our experimental results show that DeQED significantly outperformed other incomplete DCOP algorithms for both random and structured instances.