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We present in this paper a new, complete method for distributed constraint optimization, based on dynamic programming. It is a utility propagation method, inspired by the sum-product algorithm, which is correct only for tree-shaped constraint networks. In this paper, we show how to extend that algorithm to arbitrary topologies using a pseudotree arrangement(More)
This paper considers the problem of performing decentralised coordination of low-power embedded devices (as is required within many environmental sensing and surveillance applications). Specifically , we address the generic problem of maximising social welfare within a group of interacting agents. We propose a novel representation of the problem, as a(More)
We present a parameterized approximation scheme for distributed com-binatorial optimization problems based on dynamic programming. The algorithm is a utility propagation method and requires a linear number of messages. For exact computation, the size of the largest message is exponential in the width of the constraint graph. We present a distributed(More)
Multi Agent Systems (MAS) have recently attracted a lot of interest because of their ability to model many real life scenarios where information and control are distributed among a set of different agents. Practical applications include resource allocation , distributed control, scheduling, planning, etc. A major challenge in such systems is coordinating(More)
We model social choice problems in which self interested agents with private utility functions have to agree on values for a set of variables subject to side constraints. The goal is to implement the efficient solution, maximizing the total utility across all agents. Existing techniques for this problem fall into two groups. Distributed constraint(More)
Distributed constraint optimization (DCOP) provides a framework for coordinated decision making by a team of agents. Often, during the decision making, capacity constraints on agents' resource consumption must be taken into account. To address such scenarios, an extension of DCOP-Resource Constrained DCOP-has been proposed. However, certain type of(More)
We present in this paper a new complete method for distributed constraint optimization. This is a utility-propagation method, inspired by the sum-product algorithm [6]. The original algorithm requires fixed message sizes, linear memory, and is time-linear in the size of the problem. However, it is correct only for tree-shaped constraint networks. In this(More)