Reinforcement Learning (RL) is analyzed here as a tool for control system optimization. State and action spaces are assumed to be continuous. Time is assumed to be discrete, yet th...
We present a scheme to guarantee that the execution of real-time tasks can tolerate transient and intermittent faults assuming any queue- based scheduling technique. The scheme is...
A distributed protocol is proposed for the synchronization of real-time tasks that have variable resource requirements. The protocol is simple to implement and is intended for lar...
Abstract. Two-player zero-sum games are a well-established model for synthesising controllers that optimise some performance criterion. In such games one player represents the cont...
Marta Z. Kwiatkowska, Gethin Norman, Ashutosh Triv...
— This paper studies consensus seeking over noisy networks with time-varying noise statistics. Stochastic approximation type algorithms can ensure consensus in mean square and wi...