Adversarial classification: An adversarial risk analysis approach

Classification problems in security settings are usually contemplated as confrontations in which one or more adversaries try to fool a classifier to obtain a benefit. Most approaches to such adversarial classification problems have focused on game theoretical ideas with strong underlying common knowledge assumptions, which are actually not realistic in security domains. We provide an alternative framework to such problem based on adversarial risk analysis, which we illustrate with several examples. Computational and implementation issues are discussed.Comment: Published in the International Journal for Approximate Reasonin

Challenge 8: Digital Citizenship

Digital relations are deeply transforming our lives : from the nature of political participation to the relationship between digital and non-digital environments ; from the reorganization of the public sphere to the ethics of responsibility, transparency or inclusiveness. We are witnessing fundamental changes in the infrastructures of democracy and the emergence of new forms of digital citizenship.Peer reviewe

Multiagent systems

Our future is that of a mixed society of people and AI artifacts. A multitude of devices in our homes will need not only to make intelligent decisions, but they will also need to coordinate with each other to serve us well. Cars will have to coordinate to allow safe road crossings, avoiding accidents. Also, the industry is already beginning to integrate teams of humans and robots collaborating to solve complex problems...Peer reviewe