In this paper we present and evaluate an evolutionary approach for learning new constraint satisfaction algorithms, specifically for MAX-SAT optimisation problems. Our approach of...
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is an evolutionary algorithm for continuous vector-valued optimization. It combines indicator-based...
A fundamental problem of modelling in Systems Biology is to precisely characterise quantitative parameters, which are hard to measure experimentally. For this reason, it is common ...
Hendrik Rohn, Bashar Ibrahim, Thorsten Lenser, Tho...
This paper describes how design information, in our case UML specifications, can be used to evolve a software system and validate the consistency of such an evolution. This work c...
We study the possibility of constructing decision trees with evolutionary algorithms in order to increase their predictive accuracy. We present a self-adapting evolutionary algori...