Planning in partially observable environments remains a challenging problem, despite significant recent advances in offline approximation techniques. A few online methods have a...
Abstract. We propose a new saturation-based symbolic state-space generation algorithm for finite discrete-state systems. Based on the structure of the high-level model specificat...
Abstract. We deal with two important problems in pattern recognition that arise in the analysis of large datasets. While most feature subset selection methods use statistical techn...
The popularity and bandwidth consumption attributed to current Peer-to-Peer file-sharing applications makes the operation of these distributed systems very important for the Inte...
Abstract. Two approaches have been used to perform approximate inference in Bayesian networks for which exact inference is infeasible: employing an approximation algorithm, or appr...