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...
After an outline of the history of evolutionary algorithms, a new ( ) variant of the evolution strategies is introduced formally. Though not comprising all degrees of freedom, it i...
Object orientation and component-based development have both proven useful for the elaboration of open distributed systems. These paradigms are offered by the Creol language. Creo...
In many applications, decision making under uncertainty often involves two steps- prediction of a certain quality parameter or indicator of the system under study and the subseque...
The ability of Compressive Sensing (CS) to recover sparse signals from limited measurements has been recently exploited in computational imaging to acquire high-speed periodic and...
M. Salman Asif, Dikpal Reddy, Petros Boufounos, As...