Tags or observable features shared by a group of similar agents are effectively used in real and artificial societies to signal intentions and can be used to infer unobservable ...
In this paper, we study a novel problem Collective Active Learning, in which we aim to select a batch set of "informative" instances from a networking data set to query ...
Activity recognition is a key component for creating intelligent, multi-agent systems. Intrinsically, activity recognition is a temporal classification problem. In this paper, we...
Douglas L. Vail, Manuela M. Veloso, John D. Laffer...
Self-organising multi-agent systems provide a suitable paradigm for developing autonomic computing systems that manage themselves. Towards this goal, we demonstrate a robust, dece...
Ramachandra Kota, Nicholas Gibbins, Nicholas R. Je...
Recent advances in large-margin classification of data residing in general metric spaces (rather than Hilbert spaces) enable classification under various natural metrics, such as ...
Lee-Ad Gottlieb, Leonid Kontorovich, Robert Krauth...