9 citations · 23 across the 5 of their papers we have counts for
9 papers
Underwater Acoustic Networks for Security Risk Assessment in Public Drinking Water Reservoirs
Jörg Stork, Philip Wenzel, Severin Landwein +8
We have built a novel system for the surveillance of drinking water reservoirs using underwater sensor networks. We implement an innovative AI-based approach to detect, classify an…
Behavior-based Neuroevolutionary Training in Reinforcement Learning
Jörg Stork, Martin Zaefferer, Nils Eisler +3
In addition to their undisputed success in solving classical optimization problems, neuroevolutionary and population-based algorithms have become an alternative to standard reinfor…
CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems
Andreas Fischbach, Jan Strohschein, Andreas Bunte +4
This paper introduces CAAI, a novel cognitive architecture for artificial intelligence in cyber-physical production systems. The goal of the architecture is to reduce the implement…
Surrogate Models for Enhancing the Efficiency of Neuroevolution in Reinforcement Learning
Jörg Stork, Martin Zaefferer, Thomas Bartz-Beielstein +1
In the last years, reinforcement learning received a lot of attention. One method to solve reinforcement learning tasks is Neuroevolution, where neural networks are optimized by ev…
Prediction of neural network performance by phenotypic modeling
Alexander Hagg, Martin Zaefferer, Jörg Stork +1
Surrogate models are used to reduce the burden of expensive-to-evaluate objective functions in optimization. By creating models which map genomes to objective values, these models…
Improving NeuroEvolution Efficiency by Surrogate Model-based Optimization with Phenotypic Distance Kernels
Jörg Stork, Martin Zaefferer, Thomas Bartz-Beielstein
In NeuroEvolution, the topologies of artificial neural networks are optimized with evolutionary algorithms to solve tasks in data regression, data classification, or reinforcement…