Policy gradient (PG) reinforcement learning algorithms have strong (local) convergence guarantees, but their learning performance is typically limited by a large variance in the e...
We consider deployment problems where a mobile robotic network must optimize its configuration in a distributed way in order to minimize a steady-state cost function that depends ...
Typestate analysis determines whether a program violates a set of finite-state properties. Because the typestate-analysis problem is statically undecidable, researchers have propo...
The problem we address in this paper is how to detect an intruder moving through a polygonal space that is equipped with a camera sensor network. We propose a probabilistic sensor ...
We present empirical evidence that the distribution of e ort required to solve CSPs randomly generated at the 50% satis able point, when using a backtracking algorithm, can be app...