Exploiting features of high density wireless sensor networks represents a challenging issue. In this work, the training of a sensor network which consists of anonymous and asynchro...
Francesco Betti Sorbelli, Roberto Ciotti, Alfredo ...
During the past five years, our research group worked with a group of public school teachers to define, develop, and assess network-based support for collaborative learning in mid...
John M. Carroll, George Chin Jr., Mary Beth Rosson...
This paper intends to discuss self-organisation and learning capabilities in autonomous and cooperative holons that are part of a holonic manufacturing control system. These capabi...
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...
Temporal difference (TD) learning methods [22] have become popular reinforcement learning techniques in recent years. TD methods have had some experimental successes and have been...