This work presents a new algorithm, called Heuristically Accelerated Minimax-Q (HAMMQ), that allows the use of heuristics to speed up the wellknown Multiagent Reinforcement Learni...
Reinaldo A. C. Bianchi, Carlos H. C. Ribeiro, Anna...
Modern Bayesian Network learning algorithms are timeefficient, scalable and produce high-quality models; these algorithms feature prominently in decision support model development...
Abstract. In their search through a huge space of possible hypotheses, rule induction algorithms compare estimations of qualities of a large number of rules to find the one that ap...
Martin Mozina, Janez Demsar, Jure Zabkar, Ivan Bra...
Abstract. Most correlation clustering algorithms rely on principal component analysis (PCA) as a correlation analysis tool. The correlation of each cluster is learned by applying P...
COMIND is a tool for conceptual design of industrial products. It helps designers define and evaluate the initial design space by using search algorithms to generate sets of feasi...