41 citations · 43 across the 4 of their papers we have counts for
4 papers
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…
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,…
SPOT: An R Package For Automatic and Interactive Tuning of Optimization Algorithms by Sequential Parameter Optimization
Thomas Bartz-Beielstein
The sequential parameter optimization (SPOT) package for R is a toolbox for tuning and understanding simulation and optimization algorithms. Model-based investigations are common a…