In this investigation a robotic system’s dynamic performance is optimized for high reliability under uncertainty. The dynamic capability equations allow designers to predict the...
Alan P. Bowling, John E. Renaud, Jeremy T. Newkirk...
It has been almost two decades since the first globally tracking convergent adaptive controllers were derived for robot with dynamic uncertainties. However, the problem of concurr...
Chien-Chern Cheah, Chao Liu 0003, Jean-Jacques E. ...
Current trends in high-performance parallel computers show that fat-tree interconnection networks are one of the most popular topologies. The particular characteristics of this to...
Marina Alonso, Salvador Coll, Juan Miguel Mart&iac...
Background: Supervised learning for classification of cancer employs a set of design examples to learn how to discriminate between tumors. In practice it is crucial to confirm tha...
We present a framework for decision making under uncertainty where the priorities of the alternatives can depend on the situation at hand. We design a logic-programming language, D...