Research (Publications)

This page lists the research materials I published (publications, talks, etc.).

Rémy Chaput, Laetitia Matignon, Mathieu Guillermin
November, 2023 ICTAI2023 Conference paper
Learning to identify and settle dilemmas through contextual user preferences

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

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Clément Scheirlinck, Rémy Chaput, Salima Hassas
August, 2023 JOSS 2023 Journal article
Ethical Smart Grid: a Gym environment for learning ethical behaviours

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).

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Rémy Chaput, Jérémy Duval, Olivier Boissier, Mathieu Guillermin, Salima Hassas
July, 2023 ROIA 2023 Journal article
Learning multi-value ethical behaviours by combining symbolic judging agents and learning agents

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.

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Benoît Alcaraz, Olivier Boissier, Rémy Chaput, Christopher Leturc
May, 2023 AAMAS2023 Conference paper
AJAR: An Argumentation-based Judging Agents Framework for Ethical Reinforcement Learning

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.

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Rémy Chaput, Olivier Boissier, Mathieu Guillermin
May, 2023 ArXiv Preprint
Adaptive reinforcement learning of multi-agent ethically-aligned behaviours: the QSOM and QDSOM algorithms

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.

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Marco Tassella, Rémy Chaput, Mathieu Guillermin
May, 2023 ETHICS2023 Conference paper
Artificial Moral Advisors: enhancing human ethical decision-making

This paper presents how Artificial Intelligence could be used to help humans in their ethical decision-making tasks.

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Rémy Chaput
October, 2022 Univ Lyon 1 Thesis
PhD Thesis

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).

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Alain Mille, Rémy Chaput, Amélie Cordier
September, 2021 Tutorial PFIA 2020 Technical report
An historical perspective on XAI

A technical report that served as a preparatory document for a tutorial that we presented at PFIA (French Platform on Artificial Intelligence) 2020, organized by the AFIA (French Association for Artificial Intelligence).

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Rémy Chaput, Jérémy Duval, Olivier Boissier, Mathieu Guillermin, Salima Hassas
June, 2021 JFSMA Conference paper
Approche multi-agent combinant raisonnement et apprentissage pour un comportement éthique

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.

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Rémy Chaput, Jérémy Duval, Olivier Boissier, Mathieu Guillermin, Salima Hassas
May, 2021 AIES21 Conference paper
A Multi-Agent Approach to Combine Reasoning and Learning for an Ethical Behavior

Paper presented at the AI, Ethics, and Society conference. It presents a novel, hybrid, method to learn “ethical behaviors” by combining symbolic judgments with a Reinforcement Learning algorithm.

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Rémy Chaput, Amélie Cordier, Alain Mille
February, 2021 XAI Workshop 2021 Workshop paper
Explanations: What does it mean for humans, for machines, for man-machines interactions?

Paper presented at the Explainable Agency in AI Workshop, hosted by the 35th AAAI conference. It presents a quick review of explanation in the social sciences and in the AI communities, and proposes to move towards a User eXplainable Artificial Intelligence model (UXAI) to place the user at the center of the explanation process.

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Rémy Chaput, Olivier Boissier, Mathieu Guillermin, Salima Hassas
June, 2020 JFSMA Conference paper
Apprentissage adaptatif de comportements éthiques

Paper on adaptive learning of ethical behaviors I presented at JFSMA (French Days of Multi-Agent Systems).

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Rémy Chaput
October, 2019 IA² Oral presentation
Poster at GDR IA 2019

Poster about my Master thesis, at an AI Autumn school.

Poster
Rémy Chaput
June, 2019 Univ Lyon 1 Thesis
Master Research Internship

Master’s thesis on Evolutive learning of ethical behaviors, realized at the LIRIS lab, under the supervision of Professor Salima Hassas (LIRIS) and Professor Olivier Boissier (LaHC).

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