We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
Currently, among the fastest approaches to AI task planning we find many forward-chaining heuristic planners, as FF. Most of their good performance comes from the use of domain-i...
The LEGO Mindstorms robots provide an excellent introductory platform for students to learn computer programming. However, a major drawback is students’ lack of access to robots...
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...
While computers have defeated the best human players in many classic board games, progress in Go remains elusive. The large branching factor in the game makes traditional adversar...
Christopher Fellows, Yuri Malitsky, Gregory Wojtas...