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Luciano Cavalcante Siebert
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2020 – today
- 2024
- [j3]Andrea Agiollo, Luciano Cavalcante Siebert
, Pradeep K. Murukannaiah
From large language models to small logic programs: building global explanations from disagreeing local post-hoc explainers. Auton. Agents Multi Agent Syst. 38(2): 32 (2024) - [i9]Jan Wehner
Explaining Learned Reward Functions with Counterfactual Trajectories. CoRR abs/2402.04856 (2024) - [i8]Enrico Liscio, Luciano Cavalcante Siebert, Catholijn M. Jonker, Pradeep K. Murukannaiah:
Value Preferences Estimation and Disambiguation in Hybrid Participatory Systems. CoRR abs/2402.16751 (2024) - [i7]Angelo Caregnato-Neto, Luciano Cavalcante Siebert, Arkady Zgonnikov, Marcos Ricardo Omena de Albuquerque Máximo, Rubens Junqueira Magalhães Afonso:
ARMCHAIR: integrated inverse reinforcement learning and model predictive control for human-robot collaboration. CoRR abs/2402.19128 (2024) - 2023
- [j2]Luciano Cavalcante Siebert
Meaningful human control: actionable properties for AI system development. AI Ethics 3(1): 241-255 (2023) - [c8]Maria Luce Lupetti
Steering Stories: Confronting Narratives of Driving Automation through Contestational Artifacts. CHI 2023: 601:1-601:20 - [c7]Ashwin George, Luciano Cavalcante Siebert
Feasible Action-Space Reduction as a Metric of Causal Responsibility in Multi-Agent Spatial Interactions. ECAI 2023: 819-826 - [c6]Andrea Agiollo
The Quarrel of Local Post-hoc Explainers for Moral Values Classification in Natural Language Processing. EXTRAAMAS 2023: 97-115 - [i6]Jasper van Tilburg, Luciano Cavalcante Siebert, Jochen L. Cremer:
MARL-iDR: Multi-Agent Reinforcement Learning for Incentive-based Residential Demand Response. CoRR abs/2304.04086 (2023) - [i5]Ashwin George, Luciano Cavalcante Siebert, David A. Abbink, Arkady Zgonnikov:
Measuring Causal Responsibility in Multi-Agent Spatial Interactions with Feasible Action-Space Reduction. CoRR abs/2305.15003 (2023) - [i4]Catholijn M. Jonker, Luciano Cavalcante Siebert, Pradeep K. Murukannaiah:
Reflective Hybrid Intelligence for Meaningful Human Control in Decision-Support Systems. CoRR abs/2307.06159 (2023) - 2022
- [j1]Enrico Liscio
What values should an agent align with? Auton. Agents Multi Agent Syst. 36(1): 23 (2022) - [c5]Markus Peschl, Arkady Zgonnikov, Frans A. Oliehoek, Luciano Cavalcante Siebert:
MORAL: Aligning AI with Human Norms through Multi-Objective Reinforced Active Learning. AAMAS 2022: 1038-1046 - [c4]Luciano Cavalcante Siebert
Estimating Value Preferences in a Hybrid Participatory System. HHAI 2022: 114-127 - [i3]Markus Peschl, Arkady Zgonnikov, Frans A. Oliehoek, Luciano Cavalcante Siebert:
MORAL: Aligning AI with Human Norms through Multi-Objective Reinforced Active Learning. CoRR abs/2201.00012 (2022) - 2021
- [c3]Enrico Liscio, Michiel van der Meer, Luciano Cavalcante Siebert, Catholijn M. Jonker, Niek Mouter, Pradeep K. Murukannaiah:
Axies: Identifying and Evaluating Context-Specific Values. AAMAS 2021: 799-808 - [i2]Luciano Cavalcante Siebert, Maria Luce Lupetti, Evgeni Aizenberg, Niek Beckers, Arkady Zgonnikov, Herman Veluwenkamp, David A. Abbink, Elisa Giaccardi, Geert-Jan Houben, Catholijn M. Jonker, Jeroen van den Hoven, Deborah Forster, Reginald L. Lagendijk:
Meaningful human control over AI systems: beyond talking the talk. CoRR abs/2112.01298 (2021) - 2020
- [c2]Luciano Cavalcante Siebert
Improving Confidence in the Estimation of Values and Norms. COIN(E)@AAMAS 2020: 98-113 - [c1]Jasper van der Waa
Allocation of Moral Decision-Making in Human-Agent Teams: A Pattern Approach. HCI (7) 2020: 203-220 - [i1]Luciano Cavalcante Siebert, Rijk Mercuur, Virginia Dignum, Jeroen van den Hoven, Catholijn M. Jonker:
Improving Confidence in the Estimation of Values and Norms. CoRR abs/2004.01056 (2020)
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