Stability is a desirable characteristic for linear dynamical systems, but it is often ignored by algorithms that learn these systems from data. We propose a novel method for learn...
Despite the significant progress to extend Markov Decision Processes (MDP) to cooperative multi-agent systems, developing approaches that can deal with realistic problems remains ...
Policy Reuse is a method to improve reinforcement learning with the ability to solve multiple tasks by building upon past problem solving experience, as accumulated in a Policy Li...
Pervasive computing introduces data management requirements that must be tackled in a growingvariety of lightweight computing devices. Personal folders on chip, networks of sensor...
Recursive Conditioning, RC, is an any-space algorithm lor exact inference in Bayesian networks, which can trade space for time in increments of the size of a floating point number...