A recurring theme in AI and multiagent systems is how to select the "most desirable" elements given a binary dominance relation on a set of alternatives. Schwartz's...
Felix Brandt, Felix A. Fischer, Paul Harrenstein, ...
We discuss ASAP3, a refinement of the batch means algorithms ASAP and ASAP2. ASAP3 is a sequential procedure designed to produce a confidence-interval estimator for the expected r...
Natalie M. Steiger, Emily K. Lada, James R. Wilson...
Adaptive resonance theory (ART)describes a class of artificial neural networkarchitectures that act as classification tools whichself-organize, workin realtime, and require no ret...
Cathie LeBlanc, Charles R. Katholi, Thomas R. Unna...
Abstract. Learning algorithms relying on Gibbs sampling based stochastic approximations of the log-likelihood gradient have become a common way to train Restricted Boltzmann Machin...
We introduce a variability-intensive approach to goal decomposition that is tailored to support requirements identification for highly customizable software. The approach is based...