The community of multi-agent systems has been studying ways to improve the selection of partner agents for joint action. One of such approaches consists in estimating the trustwort...
—Reinforcement learning (RL) is a valuable learning method when the systems require a selection of control actions whose consequences emerge over long periods for which input– ...
— Implementing shared memory consistency models on top of hardware caches gives rise to the well-known cache coherence problem. The standard solution involves implementing cohere...
This paper discusses variable selection for medical decision making; in particular decisions regarding when to provide treatment and which treatment to provide. Current variable se...
Much of recent action recognition research is based on
space-time interest points extracted from video using a Bag
of Words (BOW) representation. It mainly relies on the discrimi...
Matteo Bregonzio (Queen Mary, University of London...