We propose an energy-based framework for approximating surfaces from a cloud of point measurements corrupted by noise and outliers. Our energy assigns a tangent plane to each (noi...
Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...
— We study problems related to supporting multicast connections with Quality of Service (QoS) requirements. We investigate the problem of optimal resource allocation in the conte...
Evolutionary Algorithms’ (EAs’) application to real world optimization problems often involves expensive fitness function evaluation. Naturally this has a crippling effect on ...
This paper summarises ongoing research and recent results on the development of flexible access control infrastructure for complex resource provisioning in Grid-based collaborativ...
Yuri Demchenko, Olle Mulmo, Leon Gommans, Cees de ...