The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is a variable-metric algorithm for real-valued vector optimization. It maintains a parent population...
In this paper we present neuro-evolution of neural network controllers for mobile agents in a simulated environment. The controller is obtained through evolution of hypercube encod...
—Modeling of complex phenomena such as the mind presents tremendous computational complexity challenges. The neural modeling fields theory (NMF) addresses these challenges in a n...
Research in the field of examination timetabling has developed in two directions. The first looks at applying various methodologies to induce examination timetables. The second tak...
A limited memory version of the covariance matrix adaptation evolution strategy (CMA-ES) is presented. This algorithm, L-CMA-ES, improves the space and time complexity of the CMA-...