Negative selection algorithms are immune-inspired classifiers that are trained on negative examples only. Classification is performed by generating detectors that match none of ...
In order to allow a comparison of (otherwise incomparable) sets, many evolutionary multiobjective optimizers use indicator functions to guide the search and to evaluate the perfor...
An important goal for the generative and developmental systems (GDS) community is to show that GDS approaches can compete with more mainstream approaches in machine learning (ML)....
Energy consumption and heat dissipation have become key considerations for modern high performance computer systems. In this paper, we focus on non-clairvoyant speed scaling to mi...
Complex and dynamic interaction behaviors in applications such as Virtual Reality (VR) systems are difficult to design and develop. Reasons for this include the complexity and lim...