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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)

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)

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)

Self stabilization in distributed systems is the ability of a system to respond to transient failures by eventually reaching a legal state, and maintaining it afterwards. This makes such systems particularly interesting because they can tolerate faults, and are able to cope with dynamic environments. We propose the first self stabilizing mechanism for… (More)

We propose ODPOP, a new distributed algorithm for open multiagent combinatorial optimization that feature unbounded domains (Faltings & Macho-Gonzalez 2005). The ODPOP algorithm explores the same search space as the dynamic programming algorithm DPOP (Petcu & Faltings 2005b) or ADOPT (Modi et al. 2005), but does so in an in-cremental, best-first fashion… (More)

- Adrian Petcu, Boi Faltings
- 2005

We define the distributed, continuous-time combinatorial optimization problem. We propose a general, semantically well-defined notion of solution stability in such systems, based on the cost of change from an already implemented solution to the new one. This approach allows maximum flexibility in specifying these costs through the use of stability… (More)

In distributed constraint optimization problems, dynamic programming methods have been recently proposed (e.g. DPOP). In dynamic programming many valuations are grouped together in fewer messages, which produce much less networking overhead than search. Nevertheless, these messages are exponential in size. The basic DPOP always communicates all possible… (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)