Reinforcement learning can provide a robust and natural means for agents to learn how to coordinate their action choices in multiagent systems. We examine some of the factors that...
Abstract. Multi-attribute negotiation has been extensively studied from a gametheoretic viewpoint. In negotiation settings, utility functions are used to express agent preferences....
Abstract. One of the key problems in model-based reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large relational domains, in wh...
Network virtualization allows one to build dynamic distributed systems in which resources can be dynamically allocated at locations where they are most useful. In order to fully e...
Dushyant Arora, Marcin Bienkowski, Anja Feldmann, ...
We consider a multi-criteria control problem that arises in a delay tolerant network with two adversarial controllers: the source and the jammer. The source's objective is to ...