Bounded approximate decentralised coordination via the max-sum algorithm

In this paper we propose a novel approach to decentralised coordination, that is able to efficiently compute solutions with a guaranteed approximation ratio. Our approach is based on a factor graph representation of the constraint network. It builds a tree structure by eliminating dependencies between the functions and variables within the factor graph that have the least impact on solution quality. It then uses the max-sum algorithm to optimally solve the resulting tree structured constraint network, and provides a bounded approximation specific to the particular problem instance. In addition, we present two generic pruning techniques to reduce the amount of computation that agents must perform when using the max-sum algorithm. When this is combined with the above mentioned approximation algorithm, the agents are able to solve decentralised coordination problems that have very large action spaces with a low computation and communication overhead. We empirically evaluate our approac...

• Type: Journal
• Year: 2011
• Where: AI
• Authors: Alex Rogers, Alessandro Farinelli, Ruben Stranders, Nicholas R. Jennings
• Keywords: AI 2011, Artificial Intelligence, Constraint Network, Factor Graph, Pruning Techniques