machine-ethics

Reinforcement learning (RL) is becoming more prevalent in practical domains with human implications, raising ethical questions. …

Reinforcement learning (RL) is becoming more prevalent in practical domains with human implications, raising ethical questions. …

This paper presents a novel Multi-Objective Reinforcement Learning approach to settle dilemmas, by putting humans in the loop.

Paper published in the Journal of Open-Source Software, alongside the source code for our ethical-smart-grid simulator. This simulator focuses on ethical behaviours within a Smart Grid, and is based on Gym (Reinforcement Learning).

Journal paper published at the French Artificial Intelligence Open Journal (Revue Ouverte d’Intelligence Artificielle). This works extends previous works, especially the conference paper published at JFSMA 2021.

Preprint describing two Reinforcement Learning algorithms (Q-SOM and Q-DSOM) I have developped. They focus on continuous and multi-dimensional observations and actions, and adaptation to changes in the environment.

Paper presented at the Autonomous Agents and Multiagent Systems conference. It presents the AJAR framework, which uses argumentation-based judging agents to provide rewards for Reinforcement Learning agents, according to one or several moral values. This “judgment of ethics” is used to nudge the learning agents towards an “ethical behavior”, that is, a behavior aligned with the given moral values.

Smart Grid simulator for Reinforcement Learning focusing on ethical behaviours.

PhD thesis on Learning behaviours aligned with moral values in a multi-agent system: guiding reinforcement learning with symbolic judgments, realized at the LIRIS lab, under the supervision of Professor Salima Hassas (LIRIS), Professor Olivier Boissier (LaHC), and Dr. Mathieu Guillermin (UCLy).

Paper on the ability to use a symbolic reasoning approach to judge neural learning agents, in order to reward them appropriately with respect to their ’ethical’ behavior, combining both approaches in a Hybrid method.