13 citations · 33 across the 9 of their papers we have counts for
15 papers
Measuring Successful Cooperation in Human-AI Teamwork: Development and Validation of the Perceived Cooperativity and Teaming Perception Scales
Christiane Attig, Christiane Wiebel-Herboth, Patricia Wollstadt +3
As human-AI cooperation becomes increasingly prevalent, reliable instruments for assessing the subjective quality of cooperative human-AI interaction are needed. We introduce two t…
Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics
Leonard Hinckeldey, Elliot Fosong, Rimvydas Rubavicius +6
As embodied autonomous systems capable of assisting humans in daily activities remain a major goal for robotics, efficient and appropriate reinforcement learning (RL) simulation te…
A Real-World Energy Management Dataset from a Smart Company Building for Optimization and Machine Learning
Jens Engel, Andrea Castellani, Patricia Wollstadt +9
We present a large real-world dataset obtained from monitoring a smart company facility over the course of six years, from 2018 to 2023. The dataset includes energy consumption dat…
Partial Information Decomposition for Continuous Variables based on Shared Exclusions: Analytical Formulation and Estimation
David A. Ehrlich, Kyle Schick-Poland, Abdullah Makkeh +3
Describing statistical dependencies is foundational to empirical scientific research. For uncovering intricate and possibly non-linear dependencies between a single target variable…
Precision and Recall Reject Curves for Classification
Lydia Fischer, Patricia Wollstadt
For some classification scenarios, it is desirable to use only those classification instances that a trained model associates with a high certainty. To obtain such high-certainty i…
Understanding Concept Identification as Consistent Data Clustering Across Multiple Feature Spaces
Felix Lanfermann, Sebastian Schmitt, Patricia Wollstadt
Identifying meaningful concepts in large data sets can provide valuable insights into engineering design problems. Concept identification aims at identifying non-overlapping groups…