AJAR: An Argumentation-based Judging Agents Framework for Ethical Reinforcement Learning
Benoît Alcaraz, Olivier Boissier, Rémy Chaput, Christopher Leturc
May, 2023
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Conference paper
Abstract
An increasing number of socio-technical systems embedding Artificial
Intelligence (AI) technologies are deployed, and questions arise about the
possible impact of such systems onto humans. We propose a hybrid multi-agent
Reinforcement Learning framework consists of learning agents that learn a
task-oriented behaviour defined by a set of symbolic moral judging agents to
ensure they respect moral values. This framework is applied on the problem of
responsible energy distribution for smart grids.
Type:
Conference paper
Publication:
AAMAS ‘23: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems
Argumentation
Hybrid Neural-Symbolic Learning
Machine Ethics
Ethical Judgment
Artificial Moral Agent
Reinforcement Learning