In this paper, we propose a Quantified Distributed Constraint Optimization problem (QDCOP) that extends the framework of Distributed Constraint Optimization problems (DCOPs). DCOP...
We investigate some approaches to solving nonconvex global optimization problems by convex nonlinear programming methods. We assume that the problem becomes convex when selected va...
This paper examines a method of clustering within a fully decentralized multi-agent system. Our goal is to group agents with similar objectives or data, as is done in traditional ...
Elth Ogston, Benno J. Overeinder, Maarten van Stee...
We propose to increment a statistical shape model with surrogate variables such as anatomical measurements and patient-related information, allowing conditioning the shape distribu...
This paper presents a decentralized task allocation method that can handle allocation of tasks with time and precedence constraints in a multi-agent setting where not all informat...
Mark Hoogendoorn, Maria L. Gini, Catholijn M. Jonk...