127 citations · 137 across the 4 of their papers we have counts for
4 papers
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…
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…
Meaningful human control: actionable properties for AI system development
Luciano Cavalcante Siebert, Maria Luce Lupetti, Evgeni Aizenberg +10
How can humans remain in control of artificial intelligence (AI)-based systems designed to perform tasks autonomously? Such systems are increasingly ubiquitous, creating benefits -…