The field of multi-agent system (MAS) is an active area of research within artificial
intelligence, with an increasingly important impact in industrial and other real-world …

Intelligent agents is a research area of the Artificial Intelligence intensely studied since the
1980s. Multi-agent systems represent a powerful paradigm of analyzing, projecting, and …

Research on optimization in multi-agent systems (MASs) has contributed with a wealth of
techniques to solve many of the challenges arising in a wide range of multi-agent …

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 …

The Internet of Things equips citizens with a phenomenal new means for online participation
in sharing economies. When agents self-determine options from which they choose, for …

Distributed problem solving is a subfield within multiagent systems, where agents are
assumed to be part of a team and collaborate with each other to reach a common goal. In …

We propose a distributed upper confidence bound approach, DUCT, for solving distributed
constraint optimization problems. We compare four variants of this approach with a baseline …

This is the first of two papers presenting and evaluating the power of a new framework for
combinatorial optimization in graphical models, based on AND/OR search spaces. We …

Abstract Distributed Constraint Optimization Problems (DCOPs) are an elegant model for
representing and solving many realistic combinatorial problems that are distributed by …

The demand for automated decision making, learning and inference in uncertain, risk
sensitive and dynamically changing situations presents a challenge: to design …