In the course of the recent complexification and sophistication of commercial computer games, the creation of competitive artificial players that are able to behave intelligentl...
Steffen Priesterjahn, Alexander Weimer, Markus Ebe...
In order to solve nonstationary optimization problems efficiently, evolutionary algorithms need sufficient diversity to adapt to environmental changes. The dual-population genetic...
Abstract. New methods of data collection, in particular the wide range of sensors and sensor networks that are being constructed, with the ability to collect real-time data streams...
We introduce a novel active learning algorithm for classification of network data. In this setting, training instances are connected by a set of links to form a network, the label...
Standard Reinforcement Learning (RL) aims to optimize decision-making rules in terms of the expected return. However, especially for risk-management purposes, other criteria such ...