The inherent and increasing complexity, heterogeneity and unpredictability of computer networks make the task of managing these systems highly complex. The autonomic computing para...
Romildo Martins da Silva Bezerra, Joberto Sé...
We present a new framework for information cue rendering on 2D vibrotactile arrays, and we describe an experiment that investigated the feasibility of our approach. The methods ar...
—This paper proposes a technique for motion estimation of groups of targets based on evolving graph networks. The main novelty over alternative group tracking techniques stems fr...
Amadou Gning, Lyudmila Mihaylova, Simon Maskell, S...
Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...
We propose a framework for quantitative security analysis of machine learning methods. Key issus of this framework are a formal specification of the deployed learning model and a...