This work deals with trajectory optimization for a network of robotic sensors sampling a spatio-temporal random field. We examine the problem of minimizing over the space of networ...
This paper considers consensus problems with delayed noisy measurements, and stochastic approximation is used to achieve mean square consensus. For stochastic approximation based c...
This research concerns fundamental performance limitations in control of discrete time nonlinear systems. The fundamental limitations are expressed in terms of the average cost of ...
Abstract-- We consider reinforcement learning, and in particular, the Q-learning algorithm in large state and action spaces. In order to cope with the size of the spaces, a functio...
Abstract-- Autonomous underwater vehicles are flexible mobile platforms for ocean sampling and surveillance missions. However, navigation of these vehicles in unstructured, highly ...