
L. (Luciano) Cavalcante Siebert
L. (Luciano) Cavalcante Siebert
Profile
Research
Siebert’s research interests are mainly focused on the interaction of humans as a society and technology. As a postdoctoral researcher at the AiTech initiative, his research deals with the incorporation of contextual aspects such as ethical norms, cognition biases, and meta-reasoning into autonomous systems, using a combination of human-like reasoning and machine learning techniques. The main goal is to support the development of autonomous systems that act under Meaningful Human Control.
Biography
Luciano Cavalcante Siebert is a postdoctoral researcher at the AiTech initiative of the Delft University of Technology. Siebert studied Mechatronics at PUCPR (B.Sc.) and did his M.Sc. and Ph.D. studies at the Federal University (UFPR), Brazil. During the development of his Ph.D. in electrical engineering, which focused on consumer behavior modeling using insights from behavioral economics, he also acted as a guest researcher at the Eindhoven University of Technology (TU/e). He has 8 years of experience in research on robotics, machine learning, optimization and automation for smart power grids. Siebert is located at the Interactive Intelligence Group of the Faculty of Electrical Engineering, Mathematics and Computer Science.
Expertise
Publications
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2023
Feasible Action-Space Reduction as a Metric of Causal Responsibility in Multi-Agent Spatial Interactions
Ashwin George / Luciano Cavalcante Siebert / David Abbink / Arkady Zgonnikov
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2023
MARL-iDR
Multi-Agent Reinforcement Learning for Incentive-Based Residential Demand Response
Jasper van Tilburg / Luciano C. Siebert / Jochen L. Cremer -
2023
Normative uncertainty and societal preferences
The problem with evaluative standards
Sietze Kai Kuilman / Koji Andriamahery / Catholijn M. Jonker / Luciano Cavalcante Siebert -
2023
Steering Stories
Confronting Narratives of Driving Automation through Contestational Artifacts
Maria Luce Lupetti / Luciano Cavalcante Siebert / David Abbink -
2023
The Quarrel of Local Post-hoc Explainers for Moral Values Classification in Natural Language Processing
Andrea Agiollo / Luciano Cavalcante Siebert / Pradeep Kumar Murukannaiah / Andrea Omicini
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