In recent years, the evolution of artificial neural networks or neuroevolution has brought promising results in solving difficult reinforcement learning problems. But, like standa...
In this work we extend the work of Dean, Kaelbling, Kirman and Nicholson on planning under time constraints in stochastic domains to handle more complicated scheduling problems. I...
We introduce a new class of control problems in which the gain depends on the solution of a stochastic differential equation reflected at the boundary of a bounded domain, along d...
We consider Voronoi-like partitions for a team of moving targets distributed in the plane, such that each set in this partition is uniquely associated with a particular moving targ...
TCP can perform poorly in multi-hop wireless networks due to problems that arise with contention and mobility. Endto-end protocols are at an inherent disadvantage in trying to sol...