Background: Dynamic modeling of metabolic reaction networks under in vivo conditions is a crucial step in order to obtain a better understanding of the (dis)functioning of living ...
I. Emrah Nikerel, Wouter A. van Winden, Walter M. ...
Currently several computational problems require high processing power to handle huge amounts of data, although underlying core algorithms appear to be rather simple. Especially i...
Lars Wienbrandt, Stefan Baumgart, Jost Bissel, Car...
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
The best performing algorithms for a particular oversubscribed scheduling application, Air Force Satellite Control Network (AFSCN) scheduling, appear to have little in common. Yet...
Laura Barbulescu, Adele E. Howe, L. Darrell Whitle...
The ideas proposed in this work are aimed to describe a novel approach based on artificial life (alife) environments for on-line adaptive optimisation of dynamical systems. The bas...
Mauro Annunziato, Ilaria Bertini, M. Lucchetti, Al...