The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Studying the evolution of long lived processes such as the development history of a software system or the publication history of a research community, requires the analysis of a ...
Typical applications of evolutionary optimization in static environments involve the approximation of the extrema of functions. For dynamic environments, the interest is not to lo...
This paper presents a methodology for using heuristic search methods to optimise cancer chemotherapy. Specifically, two evolutionary algorithms - Population Based Incremental Lear...
Andrei Petrovski, Siddhartha Shakya, John A. W. Mc...
The ever increasing usage of microprocessor devices is sustained by a high volume production that in turn requires a high production yield, backed by a controlled process. Fault d...