Decentralised coordination of continuously valued control parameters using the max-sum algorithm

In this paper we address the problem of decentralised coordination for agents that must make coordinated decisions over continuously valued control parameters (as is required in many real world applications). In particular, we tackle the social welfare maximisation problem, and derive a novel continuous version of the max-sum algorithm. In order to do so, we represent the utility function of the agents by multivariate piecewise linear functions, which in turn are encoded as simplexes. We then derive analytical solutions for the fundamental operations required to implement the max-sum algorithm (specifically, addition and marginal maximisation of general n-ary piecewise linear functions). We empirically evaluate our approach on a simulated network of wireless, energy constrained sensors that must coordinate their sense/sleep cycles in order to maximise the system-wide probability of event detection. We compare the conventional discrete max-sum algorithm with our novel continuous versi...

• Type: Conference
• Year: 2009
• Where: ATAL
• Authors: Ruben Stranders, Alessandro Farinelli, Alex Rogers, Nick R. Jennings
• Keywords: Artificial Intelligence, ATAL 2009, Max-sum Algorithm, Piecewise Linear Functions, Welfare Maximisation Problem