Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...
This paper considers online stochastic optimization problems where time constraints severely limit the number of offline optimizations which can be performed at decision time and/...
Combinatorial optimization games form an important subclass of cooperative games. In recent years, increased attention has been given to the issue of finding good cost shares for...
Underwater sensor networks consist of sensors and vehicles deployed to perform collaborative monitoring tasks over a given region. Underwater sensor networks will find applicatio...
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 ...