… the two challenges to DCOP raised above. We … DCOP and prove the congruency and
optimality of our formulations. When all constraints involve only two agents, we can model DCOP …

… model of the DCOP framework. In Section 3, we introduce a decomposition of the DCOP into
a … We prove that the optimal solution of the DCOP is a Nash equilibrium in an appropriate …

… problems modelled as distributed constraint optimization (DCOP). However, there are only
few … In the present work we compare three complete algorithms for DCOP, aiming at studying …

… DCOP problem is a problem where several agents coordinate their values such that the sum
of the resulting constraint costs is minimal. It is often desirable to solve DCOP … DCOP search …

We consider environments in which smart devices equipped with limited communication
and computation capabilities have to cooperate to selfconfigure their state in an energy-efficient …

With the growing complexity of the current power grid, there is an increasing need for
intelligent operations coordinating energy supply and demand. A key feature of the smart grid …

… DCOP. In this paper, we investigate how to maximize the amount of information reuse by
DCOP … -space DCOP search algorithms to reuse information gained from solving the previous …

… Optimization Problems (DCOP) have emerged as key … DCOP algorithm. We investigate
when preprocessing is useful and which factors influence the resulting speedups in two DCOP …

… DCOP-based approach by describing a case study taken from the RoboCare project. More
specifically, we show how (1) DCOP … from other algorithms for DCOP represent a strong asset …

… One can transform a general DCOP to our restricted DCOP using pre-processing … graph
visualizes a DCOP instance, where nodes in the graph correspond to variables in the DCOP and …