The problem of making sequential decisions in unknown probabilistic environments is studied. In cycle t action yt results in perception xt and reward rt, where all quantities in g...
Security decision-making is hard for both humans and machines. This is because security decisions are context-dependent, require highly dynamic, specialized knowledge, and require...
For supervised learning, feature selection algorithms attempt to maximise a given function of predictive accuracy. This function usually considers the ability of feature vectors t...
Abstract. We describe a novel decision procedure for Quantified Boolean Formulas (QBFs) which aims to unleash the hidden potential of quantified reasoning in applications. The Sk...
We propose a new rule induction algorithm for solving classification problems via probability estimation. The main advantage of decision rules is their simplicity and good interp...