We consider the problem of learning a finite automaton M of n states with input alphabet X and output alphabet Y when a teacher has helpfully or randomly labeled the states of M u...
Dana Angluin, Leonor Becerra-Bonache, Adrian Horia...
In this paper we consider the problem of policy evaluation in reinforcement learning, i.e., learning the value function of a fixed policy, using the least-squares temporal-differe...
Alessandro Lazaric, Mohammad Ghavamzadeh, Ré...
We present a new control design method for perturbed multiple-input systems, which guarantees any desired componentwise ultimate bound on the system state. The method involves eig...
Abstract-- We present a computational framework for automatic synthesis of a feedback control strategy for a piecewise affine (PWA) system from a specification given as a Linear Te...
Jana Tumova, Boyan Yordanov, Calin Belta, Ivana Ce...
— This paper presents a control for state-constrained nonlinear systems in strict feedback form to achieve output tracking. To prevent states from violating the constraints, we e...