Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
This paper sums up lessons learned from a sequence of cooperative design workshops where end users were enabled to design mobile systems through scenario building, role playing, a...
This paper presents a new hierarchical simulation algorithm allowing the calculation of radiosity solutions for time-dependent scenes where all motion is known a priori. Such solut...
Grid computing gives users access to widely distributed networks of computing resources to solve large-scale tasks such as scientific computation. These tasks are defined as stand...
Jim Blythe, Ewa Deelman, Yolanda Gil, Carl Kesselm...
Abstract— Kinodynamic planning algorithms like RapidlyExploring Randomized Trees (RRTs) hold the promise of finding feasible trajectories for rich dynamical systems with complex...