Nature-Inspired Computing
We study nature inspired algorithms and techniques such as evolutionary algorithms and (deep) neural networks. Evolutionary algorithms have applications in optimization including multi-objective optimization. We study evolutionary algorithms for expensive optimization, that is, optimization problems where the objective functions are slow or expensive to evaluate. Additionally, we apply evolutionary algorithms in the area of neural architecture search and automated machine learning.
contact: doc. Mgr. Martin Pilát, Ph.D.