We consider the classical finite-state discounted Markovian decision problem, and we introduce a new policy iteration-like algorithm for finding the optimal state costs or Q-facto...
In the past decade, moving horizon estimation (MHE) has emerged as a powerful technique for estimating the state of a dynamical system in the presence of nonlinearities and disturb...
Angelo Alessandri, Marco Baglietto, Giorgio Battis...
Round-based games are an instance of discrete planning problems. Some of the best contemporary game tree search algorithms use random roll-outs as data. Relying on a good policy, ...
Image restoration problems are often converted into large-scale, nonsmooth and nonconvex optimization problems. Most existing minimization methods are not efficient for solving su...
—In this work we address the problem of state estimation in dynamical systems using recent developments in compressive sensing and sparse approximation. We formulate the traditio...
Adam Charles, Muhammad Salman Asif, Justin K. Romb...