A Hybrid Continuous Max-Sum Algorithm for Decentralised Coordination

Abstract. In this paper we tackle the problem of coordinating multiple decentralised agents with continuous state variables. Specifically we propose a hybrid approach, which combines the maxsum algorithm with continuous non-linear optimisation methods. We show that, for problems with acyclic factor graph representations, for suitable parameter choices and sufficiently fine state space discretisations, our proposed algorithm converges to a state with utility close to the global optimum. We empirically evaluate our approach for cyclic constraint graphs in a multi-sensor target classification problem, and compare its performance to the discrete max-sum algorithm, as well as a non-coordinated approach and the distributed stochastic algorithm (DSA). We show that our hybrid max-sum algorithm outperforms the non-coordinated algorithm, DSA and discrete max-sum by up to 40% in this problem domain. Furthermore, the improvements in outcome over discrete max-sum come without significant increases ...

• Type: Journal
• Year: 2010
• Where: ECAI
• Authors: Thomas Voice, Ruben Stranders, Alex Rogers, Nicholas R. Jennings
• Keywords: Algorithm, Artificial Intelligence, Discrete Max-sum, ECAI 2010, Max-sum Algorithm