Abstract—As the number of wireless sensor network applications continues to grow, the need for specialized task scheduling mechanisms, aware of the sensor devices’ capabilities...
Tim De Pauw, Stijn Verstichel, Bruno Volckaert, Fi...
Aggregate traffic loads and topology in multi-hop wireless networks may vary slowly, permitting MAC protocols to `learn' how to spatially coordinate and adapt contention patte...
Abstract. In the multiagent meeting scheduling problem, agents negotiate with each other on behalf of their users to schedule meetings. While a number of negotiation approaches hav...
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
: The development of new Information Technologies have originated new possibilities to develop pedagogical methodologies that provide the necessary knowledge and skills in the High...