8 citations · 14 across the 6 of their papers we have counts for
6 papers
Value Preferences Estimation and Disambiguation in Hybrid Participatory Systems
Enrico Liscio, Luciano C. Siebert, Catholijn M. Jonker +1
Understanding citizens' values in participatory systems is crucial for citizen-centric policy-making. We envision a hybrid participatory system where participants make choices and…
Reflective Hybrid Intelligence for Meaningful Human Control in Decision-Support Systems
Catholijn M. Jonker, Luciano Cavalcante Siebert, Pradeep K. Murukannaiah
With the growing capabilities and pervasiveness of AI systems, societies must collectively choose between reduced human autonomy, endangered democracies and limited human rights, a…
Feasible Action-Space Reduction as a Metric of Causal Responsibility in Multi-Agent Spatial Interactions
Ashwin George, Luciano Cavalcante Siebert, David Abbink +1
Modelling causal responsibility in multi-agent spatial interactions is crucial for safety and efficiency of interactions of humans with autonomous agents. However, current formal m…
MARL-iDR: Multi-Agent Reinforcement Learning for Incentive-based Residential Demand Response
Jasper van Tilburg, Luciano C. Siebert, Jochen L. Cremer
This paper presents a decentralized Multi-Agent Reinforcement Learning (MARL) approach to an incentive-based Demand Response (DR) program, which aims to maintain the capacity limit…
MORAL: Aligning AI with Human Norms through Multi-Objective Reinforced Active Learning
Markus Peschl, Arkady Zgonnikov, Frans A. Oliehoek +1
Inferring reward functions from demonstrations and pairwise preferences are auspicious approaches for aligning Reinforcement Learning (RL) agents with human intentions. However, st…
Improving Confidence in the Estimation of Values and Norms
Luciano Cavalcante Siebert, Rijk Mercuur, Virginia Dignum +2
Autonomous agents (AA) will increasingly be interacting with us in our daily lives. While we want the benefits attached to AAs, it is essential that their behavior is aligned with…