Abstract. Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist several convergent and consistent RL algorithms which have been intensivel...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...
Research on organization of Multi-Agent Systems (M.A.S.) has shown that by adapting its organization, a M.A.S. is better able to operate in dynamic environments. In this paper we ...
Mattijs Ghijsen, Wouter N. H. Jansweijer, Bob J. W...
Abstract. Real market institutions, stock and commodity exchanges for example, do not occur in isolation. Company stock is frequently listed on several stock exchanges, allowing tr...
Jinzhong Niu, Kai Cai, Simon Parsons, Elizabeth Sk...
Multiagent systems for mobile and pervasive computing should extensively exploit contextual information both to adapt to user needs and to enable autonomic behavior. This raises th...
Gabriella Castelli, Marco Mamei, Franco Zambonelli
General trust management model that we present is adapted for ad-hoc coalition environment, rather than for classic client-supplier relationship. The trust representation used in ...