Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
In this paper we combine two existing resource selection approaches, CORI and the decision-theoretic framework (DTF). The state-of-the-art system CORI belongs to the large group of...
Abstract. Many real world problems are given in the form of multiple measurements comprising local descriptions or tasks. We propose that a dynamical organization of a population o...
We investigate a series of graph-theoretic constraints on non-projective dependency parsing and their effect on expressivity, i.e. whether they allow naturally occurring syntactic...
In this paper, a modified fuzzy system modelling algorithm that incorporates Type 2 fuzzy sets, which is based on intervalvalued membership degrees rather than singleton membershi...