Next-generation autonomous agents will be expected to converse with people to achieve their mutual goals. Human-machine dialogue, however, is challenged by noisy acoustic data, and by people’s preference for more natural interaction. This paper describes an ambitious project that embeds human subjects in a spoken dialogue system. It collects a rich and novel data set, including spoken dialogue,...

We present an architectural framework for systematically using automated diversity to provide high assurance detection and disruption for large classes of attacks. The framework executes a set of automatically diversified variants on the same inputs, and monitors their behavior to detect divergences. The benefit of this approach is that it requires an attacker to simultaneously compromise all s...

I very much enjoyed reading this paper. The basic message that I took away was that by and large different banks rate a given borrower in pretty much the same way. While we do see differences, on the whole at least to my eye these differences are generally small. I therefore read the paper as basically good news for the New Basel Capital Accord. If we want to worry about any of the results in t...

It is an accepted fact of academic life that some papers, in whatever discipline and wherever published, will never be cited. Empirical support for this can be found in studies such as those reported by Glanzel (1992), Rousseau (1994), and Egghe (2000) where the distribution of the time of first citation is investigated. In all cases, it is assumed that never-citation is connected with the perc...

data envelopment analysis (dea) is a method for measuring the relative efficiencies of a set of decision-making units (dmus) that use multiple inputs to produce multiple outputs. in this paper, we study the measurement of dmu performances in dea in situations where input and/or output values are given as imprecise data. by imprecise data we mean situations where we only know that the actual val...