Up-to-date results on the application of Markov models to chromosome analysis are presented. On the one hand, this means using continuous Hidden Markov Models (HMMs) instead of dis...
In this paper, we study an adaptive random search method based on continuous action-set learning automaton for solving stochastic optimization problems in which only the noisecorr...
Abstract. Many techniques in model-based diagnosis and other research fields find the hitting sets of a group of sets. Existing techniques apply to sets of finite elements only. Th...
With the number of attacks on systems increasing, it is highly probable that sooner or later an intrusion will be successful. Not having to execute a complete shutdown in this sit...
Approximate linear programming (ALP) offers a promising framework for solving large factored Markov decision processes (MDPs) with both discrete and continuous states. Successful ...