Predictive state representations (PSRs) are a recently proposed way of modeling controlled dynamical systems. PSR-based models use predictions of observable outcomes of tests that...
Reduced models have long been used as a tool for the analysis of the complex activity taking place in neurons and their coupled networks. Recent advanced in experimental and theore...
—A high performance adaptive robust control (ARC) algorithm is developed for a class of nonlinear system with unknown input backlash, parametric uncertainties and uncertain nonli...
In dangerous and uncertain environments initial plans must be revised. Communication failures hamper this replanning. We introduce fractured subteams as a novel formalism for mode...
In this paper, it is shown how to extract a hypothesis with small risk from the ensemble of hypotheses generated by an arbitrary on-line learning algorithm run on an independent an...