9 citations · 15 across the 6 of their papers we have counts for
6 papers
Optimization of High-dimensional Simulation Models Using Synthetic Data
Thomas Bartz-Beielstein, Eva Bartz, Frederik Rehbach +1
Simulation models are valuable tools for resource usage estimation and capacity planning. In many situations, reliable data is not available. We introduce the BuB simulator, which…
Simulation of an Elevator Group Control Using Generative Adversarial Networks and Related AI Tools
Tom Peetz, Sebastian Vogt, Martin Zaefferer +1
Testing new, innovative technologies is a crucial task for safety and acceptance. But how can new systems be tested if no historical real-world data exist? Simulation provides an a…
Expected Improvement versus Predicted Value in Surrogate-Based Optimization
Frederik Rehbach, Martin Zaefferer, Boris Naujoks +1
Surrogate-based optimization relies on so-called infill criteria (acquisition functions) to decide which point to evaluate next. When Kriging is used as the surrogate model of choi…
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…
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…
Evaluation of Cognitive Architectures for Cyber-Physical Production Systems
Andreas Bunte, Andreas Fischbach, Jan Strohschein +3
Cyber-physical production systems (CPPS) integrate physical and computational resources due to increasingly available sensors and processing power. This enables the usage of data,…