Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Machine Learning in Human-Robot Collaboration: Bridging the Gap
3
Zitationen
6
Autoren
2022
Jahr
Abstract
This workshop aims to bring together researchers to explore and identify ways in which human-robot collaboration can reap the benefits of modern machine learning. The intended outcome is a roadmap that identifies key milestones that will lead us towards fluent effective human-robot teaming. In addition to focus groups and creative brainstorming exercises, this workshop will comprise invited talks, contributed paper talks, a poster session, and a debate. The papers, talks, posters, and roadmap will be made publicly available on our website: https://sites.google.com/view/mlhrc-hri-2022/home.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.445 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.325 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.761 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.530 Zit.