Partially Observable Markov Decision Processes have been studied widely as a model for decision making under uncertainty, and a number of methods have been developed to find the s...
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...
: Given a continuous-time controller and a Lyapunov function that shows global asymptotic stability for the closed loop system, we provide several results for modification of the c...
Recently, the generalization framework in co-evolutionary learning has been theoretically formulated and demonstrated in the context of game-playing. Generalization performance of...
This work studies the optimality and stability of timing-driven placement algorithms. The contributions of this work include two parts: 1) We develop an algorithm for generating s...