Multi-agent systems are an increasingly important software paradigm and in many of its applications agents cooperate to achieve a particular goal. This requires the design of effi...
Taolue Chen, Marta Z. Kwiatkowska, David Parker, A...
Learning in a multiagent system is a challenging problem due to two key factors. First, if other agents are simultaneously learning then the environment is no longer stationary, t...
Abstract. Online games and location-based services now form the potential application domains for the P2P paradigm. In P2P systems, balancing the workload is essential for overall ...
Mohammed Eunus Ali, Egemen Tanin, Rui Zhang, Lars ...
We offer a new formal criterion for agent-centric learning in multi-agent systems, that is, learning that maximizes one’s rewards in the presence of other agents who might also...
We initiate the study of an interesting aspect of sponsored search advertising, namely the consequences of broad match- a feature where an ad of an advertiser can be mapped to a b...