Greedy search is commonly used in an attempt to generate solutions quickly at the expense of completeness and optimality. In this work, we consider learning sets of weighted actio...
Much like relational probabilistic models, the need for relational preference models arises naturally in real-world applications where the set of object classes is fixed, but obj...
Rough set theory can be applied to rule induction. There are two different types of classification rules, positive and boundary rules, leading to different decisions and consequen...
Generative model learning is one of the key problems in machine learning and computer vision. Currently the use of generative models is limited due to the difficulty in effective...
Abstract. The problem of self-optimization and adaptation in the context of customizable systems is becoming increasingly important with the emergence of complex software systems a...