12 citations · 15 across the 7 of their papers we have counts for
7 papers
Have I Solved This Before? Retrieving Similar Segmentation Problems for Evolutionary Learning
Andreas Margraf, Henning Cui, Jörg Hähner
Reliable integration and solid configuration of monitoring systems constitute a fundamental prerequisites for achieving high efficiency and productivity in contemporary manufacturi…
Performance and Explainability Requirements of Evolutionary Algorithms in Real-World Physics-Informed Optimization
Helena Stegherr, Michael Heider, Nils Meyer +7
Evolutionary computation offers a variety of tools to solve complex real-world optimization problems. However, research often focuses on smaller, simplified problems and optimizati…
Modernising Reinforcement Learning-Based Navigation for Embodied Semantic Scene Graph Generation
Roman Küble, Marco Hüller, Mrunmai Phatak +2
Semantic world models enable embodied agents to reason about objects, relations, and spatial context beyond purely geometric representations. In Organic Computing, such models are…
PDPK: A Framework to Synthesise Process Data and Corresponding Procedural Knowledge for Manufacturing
Richard Nordsieck, André Schweizer, Michael Heider +1
Procedural knowledge describes how to accomplish tasks and mitigate problems. Such knowledge is commonly held by domain experts, e.g. operators in manufacturing who adjust paramete…
Investigating the Impact of Independent Rule Fitnesses in a Learning Classifier System
Michael Heider, Helena Stegherr, Jonathan Wurth +2
Achieving at least some level of explainability requires complex analyses for many machine learning systems, such as common black-box models. We recently proposed a new rule-based…
Learning Classifier Systems for Self-Explaining Socio-Technical-Systems
Michael Heider, Helena Stegherr, Richard Nordsieck +1
In socio-technical settings, operators are increasingly assisted by decision support systems. By employing these, important properties of socio-technical systems such as self-adapt…
Separating Rule Discovery and Global Solution Composition in a Learning Classifier System
Michael Heider, Helena Stegherr, Jonathan Wurth +2
While utilization of digital agents to support crucial decision making is increasing, trust in suggestions made by these agents is hard to achieve. However, it is essential to prof…