Bente Riegler

University of Hertfordshire

Papers

1

Total Citations

3

H-Index

1

About

Bente Riegler is a researcher at the forefront of embodied cognition and robotics, whose work bridges the gap between theoretical models of physical intelligence and practical robotic performance. Her primary research areas include embodiment theory, decision-making architectures, and the informational costs associated with robot behavior. Riegler’s major contribution lies in developing and applying quantitative models that demonstrate how a robot’s physical form—its embodiment—directly influences the efficiency of its decision-making processes. By analyzing the trade-offs between atomic actions and scripted sequences, she has provided concrete metrics for optimizing robot design and control. Her most cited work, “Embodiment and Its Influence on Informational Costs of Decision Density,” has garnered attention for its novel approach to quantifying the advantages of well-chosen physical structures. Though early in her career, Riegler’s research is already shaping how engineers think about the interplay between hardware and software, offering a rigorous framework for designing more adaptive and efficient autonomous systems. Her work promises to redefine how we understand the role of the body in intelligent action.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Embodiment and Its Influence on Informational Costs of Decision Density—Atomic Actions vs. Scripted Sequences
3 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: University of Hertfordshire

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago