[{"content":"I am an Associate Professor in Artificial Intelligence, focusing on AI and Ethics: how to design and use systems that take ethically-aligned decisions with our moral values.\nI currently work at CPE Lyon, where I teach data science (storage, analysis) and AI (machine learning, reinforcement learning, ethical aspects of AI \u0026ndash; bias, fairness, etc.).\nI am also part of the LIRIS lab (CNRS-UMR5205), in the Cognitive Systems and Multi-Agent Systems (SyCoSMA) team, in which my research is at the intersection of hybrid neural-symbolic learning systems, reinforcement learning, explainability, and machine ethics.\n","date":"8 September 2025","externalUrl":null,"permalink":"/","section":"","summary":"","title":"","type":"page"},{"content":"This is a third-party PettingZoo environment, focusing on learning ethically-aligned behaviours in a multi-agent gardening use-case.\nSeveral agents must plant and harvest flowers in a gridworld garden, in order to satisfy several objectives that are meant as proxies for moral values. The goal is to show that, if these agents can learn the proxies, then they should be able to learn moral values once we implement them in the system.\nThe current proxies are inspired from the Sustainable Development Goals, and include: 1) gaining enough money to live comfortably, by harvesting and selling flowers; 2) ensuring the pollution decreases in the environment by planting flowers; 3) ensuring the diversity increases by keeping various species of flowers.\n","date":"8 September 2025","externalUrl":null,"permalink":"/projects/ethical-gardeners/","section":"Projects","summary":"Multi-agent gardening simulator for Reinforcement Learning focusing on ethical behaviours.","title":"ethical-gardeners","type":"projects"},{"content":"","date":"8 September 2025","externalUrl":null,"permalink":"/tags/machine-ethics/","section":"Tags","summary":"","title":"Machine Ethics","type":"tags"},{"content":"This page lists the Open-Source projects I have created or contributed to.\n","date":"8 September 2025","externalUrl":null,"permalink":"/projects/","section":"Projects","summary":"Projects I have contributed to.","title":"Projects","type":"projects"},{"content":"","date":"8 September 2025","externalUrl":null,"permalink":"/tags/python/","section":"Tags","summary":"","title":"Python","type":"tags"},{"content":"","date":"8 September 2025","externalUrl":null,"permalink":"/tags/reinforcement-learning/","section":"Tags","summary":"","title":"Reinforcement Learning","type":"tags"},{"content":"","date":"8 September 2025","externalUrl":null,"permalink":"/tags/simulator/","section":"Tags","summary":"","title":"Simulator","type":"tags"},{"content":"","date":"8 September 2025","externalUrl":null,"permalink":"/tags/smart-grid/","section":"Tags","summary":"","title":"Smart Grid","type":"tags"},{"content":"","date":"8 September 2025","externalUrl":null,"permalink":"/tags/","section":"Tags","summary":"","title":"Tags","type":"tags"},{"content":"","date":"20 October 2024","externalUrl":null,"permalink":"/authors/","section":"Authors","summary":"","title":"Authors","type":"authors"},{"content":"","date":"20 October 2024","externalUrl":null,"permalink":"/authors/la%C3%ABtitia-matignon/","section":"Authors","summary":"","title":"Laëtitia Matignon","type":"authors"},{"content":"","date":"20 October 2024","externalUrl":null,"permalink":"/tags/multi-objective-decision-making/","section":"Tags","summary":"","title":"Multi-Objective Decision Making","type":"tags"},{"content":"","date":"20 October 2024","externalUrl":null,"permalink":"/publication/modem2024/","section":"Research (Publications)","summary":"","title":"Multi-objective reinforcement learning: an ethical perspective","type":"publication"},{"content":"","date":"20 October 2024","externalUrl":null,"permalink":"/authors/r%C3%A9my-chaput/","section":"Authors","summary":"","title":"Rémy Chaput","type":"authors"},{"content":"This page lists the research materials I published (publications, talks, etc.).\n","date":"20 October 2024","externalUrl":null,"permalink":"/publication/","section":"Research (Publications)","summary":"This page lists the research materials I published (publications, talks, etc.).","title":"Research (Publications)","type":"publication"},{"content":"","date":"20 October 2024","externalUrl":null,"permalink":"/authors/timon-deschamps/","section":"Authors","summary":"","title":"Timon Deschamps","type":"authors"},{"content":"","date":"1 July 2024","externalUrl":null,"permalink":"/authors/laetitia-matignon/","section":"Authors","summary":"","title":"Laetitia Matignon","type":"authors"},{"content":"","date":"1 July 2024","externalUrl":null,"permalink":"/publication/rjcia2024/","section":"Research (Publications)","summary":"","title":"Multi-objective reinforcement learning: an ethical perspective","type":"publication"},{"content":"","date":"13 January 2024","externalUrl":null,"permalink":"/tags/argumentation/","section":"Tags","summary":"","title":"Argumentation","type":"tags"},{"content":"Argumentation Reward Designer (ARD) is a tool that helps to create reward functions based on argumentation graphs. It builds upon the AJAR library and provides a visual interface to design the graphs, by placing and moving arguments on a grid, and drawing attacks between them.\nGraphs can then be exported to JSON, PNG (for sharing a visual representation of the graph), or Python code (which can be used in https://rchaput.github.io/projects/ethical-smartgrid/).\n","date":"13 January 2024","externalUrl":null,"permalink":"/projects/argumentation-reward-designer/","section":"Projects","summary":"Helper web app to visually design argumentation graphs.","title":"argumentation-reward-designer","type":"projects"},{"content":"","date":"13 January 2024","externalUrl":null,"permalink":"/tags/graph/","section":"Tags","summary":"","title":"Graph","type":"tags"},{"content":"","date":"13 January 2024","externalUrl":null,"permalink":"/tags/js/","section":"Tags","summary":"","title":"JS","type":"tags"},{"content":"","date":"13 January 2024","externalUrl":null,"permalink":"/tags/material-ui/","section":"Tags","summary":"","title":"Material UI","type":"tags"},{"content":"","date":"13 January 2024","externalUrl":null,"permalink":"/tags/react-flow/","section":"Tags","summary":"","title":"React Flow","type":"tags"},{"content":"","date":"13 January 2024","externalUrl":null,"permalink":"/tags/react.js/","section":"Tags","summary":"","title":"React.js","type":"tags"},{"content":"","date":"13 January 2024","externalUrl":null,"permalink":"/tags/web-app/","section":"Tags","summary":"","title":"Web App","type":"tags"},{"content":"","date":"6 November 2023","externalUrl":null,"permalink":"/tags/human-preferences/","section":"Tags","summary":"","title":"Human Preferences","type":"tags"},{"content":"","date":"6 November 2023","externalUrl":null,"permalink":"/publication/ictai2023/","section":"Research (Publications)","summary":"This paper presents a novel Multi-Objective Reinforcement Learning approach to\nsettle dilemmas, by putting humans in the loop.","title":"Learning to identify and settle dilemmas through contextual user preferences","type":"publication"},{"content":"","date":"6 November 2023","externalUrl":null,"permalink":"/authors/mathieu-guillermin/","section":"Authors","summary":"","title":"Mathieu Guillermin","type":"authors"},{"content":"","date":"6 November 2023","externalUrl":null,"permalink":"/tags/moral-dilemmas/","section":"Tags","summary":"","title":"Moral Dilemmas","type":"tags"},{"content":"","date":"6 November 2023","externalUrl":null,"permalink":"/tags/multi-objective-reinforcement-learning/","section":"Tags","summary":"","title":"Multi-Objective Reinforcement Learning","type":"tags"},{"content":"","date":"25 August 2023","externalUrl":null,"permalink":"/authors/cl%C3%A9ment-scheirlinck/","section":"Authors","summary":"","title":"Clément Scheirlinck","type":"authors"},{"content":"","date":"25 August 2023","externalUrl":null,"permalink":"/publication/joss2023/","section":"Research (Publications)","summary":"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).","title":"Ethical Smart Grid: a Gym environment for learning ethical behaviours","type":"publication"},{"content":"","date":"25 August 2023","externalUrl":null,"permalink":"/tags/multi-agent-system/","section":"Tags","summary":"","title":"Multi-Agent System","type":"tags"},{"content":"","date":"25 August 2023","externalUrl":null,"permalink":"/tags/openai-gym/","section":"Tags","summary":"","title":"OpenAI Gym","type":"tags"},{"content":"","date":"25 August 2023","externalUrl":null,"permalink":"/authors/salima-hassas/","section":"Authors","summary":"","title":"Salima Hassas","type":"authors"},{"content":"","date":"4 July 2023","externalUrl":null,"permalink":"/tags/ethical-judgment/","section":"Tags","summary":"","title":"Ethical Judgment","type":"tags"},{"content":"","date":"4 July 2023","externalUrl":null,"permalink":"/tags/ethics/","section":"Tags","summary":"","title":"Ethics","type":"tags"},{"content":"","date":"4 July 2023","externalUrl":null,"permalink":"/tags/hybrid-neural-symbolic-learning/","section":"Tags","summary":"","title":"Hybrid Neural-Symbolic Learning","type":"tags"},{"content":"","date":"4 July 2023","externalUrl":null,"permalink":"/authors/j%C3%A9r%C3%A9my-duval/","section":"Authors","summary":"","title":"Jérémy Duval","type":"authors"},{"content":"","date":"4 July 2023","externalUrl":null,"permalink":"/publication/roia2023/","section":"Research (Publications)","summary":"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.","title":"Learning multi-value ethical behaviours by combining symbolic judging agents and learning agents","type":"publication"},{"content":"","date":"4 July 2023","externalUrl":null,"permalink":"/tags/multi-agent-learning/","section":"Tags","summary":"","title":"Multi-Agent Learning","type":"tags"},{"content":"","date":"4 July 2023","externalUrl":null,"permalink":"/authors/olivier-boissier/","section":"Authors","summary":"","title":"Olivier Boissier","type":"authors"},{"content":"","date":"30 May 2023","externalUrl":null,"permalink":"/publication/arxiv2023/","section":"Research (Publications)","summary":"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.","title":"Adaptive reinforcement learning of multi-agent ethically-aligned behaviours: the QSOM and QDSOM algorithms","type":"publication"},{"content":"","date":"30 May 2023","externalUrl":null,"permalink":"/publication/aamas2023/","section":"Research (Publications)","summary":"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.","title":"AJAR: An Argumentation-based Judging Agents Framework for Ethical Reinforcement Learning","type":"publication"},{"content":"","date":"30 May 2023","externalUrl":null,"permalink":"/tags/artificial-moral-agent/","section":"Tags","summary":"","title":"Artificial Moral Agent","type":"tags"},{"content":"","date":"30 May 2023","externalUrl":null,"permalink":"/tags/artificial-moral-agents/","section":"Tags","summary":"","title":"Artificial Moral Agents","type":"tags"},{"content":"","date":"30 May 2023","externalUrl":null,"permalink":"/authors/beno%C3%AEt-alcaraz/","section":"Authors","summary":"","title":"Benoît Alcaraz","type":"authors"},{"content":"","date":"30 May 2023","externalUrl":null,"permalink":"/authors/christopher-leturc/","section":"Authors","summary":"","title":"Christopher Leturc","type":"authors"},{"content":"","date":"30 May 2023","externalUrl":null,"permalink":"/tags/multi-agent-reinforcement-learning/","section":"Tags","summary":"","title":"Multi-Agent Reinforcement Learning","type":"tags"},{"content":"","date":"30 May 2023","externalUrl":null,"permalink":"/tags/multi-agent-systems/","section":"Tags","summary":"","title":"Multi-Agent Systems","type":"tags"},{"content":"","date":"18 May 2023","externalUrl":null,"permalink":"/tags/ai-moral-enhancement/","section":"Tags","summary":"","title":"AI Moral Enhancement","type":"tags"},{"content":"","date":"18 May 2023","externalUrl":null,"permalink":"/tags/artificial-moral-advisors/","section":"Tags","summary":"","title":"Artificial Moral Advisors","type":"tags"},{"content":"","date":"18 May 2023","externalUrl":null,"permalink":"/publication/ethics2023/","section":"Research (Publications)","summary":"This paper presents how Artificial Intelligence could be used to help humans\nin their ethical decision-making tasks.","title":"Artificial Moral Advisors: enhancing human ethical decision-making","type":"publication"},{"content":"","date":"18 May 2023","externalUrl":null,"permalink":"/authors/marco-tassella/","section":"Authors","summary":"","title":"Marco Tassella","type":"authors"},{"content":"This is a third-party Gym environment, focusing on learning ethically-aligned behaviours in a Smart Grid use-case.\nA Smart Grid contains several prosumer (prosumer-consumer) agents that interact in a shared environment by consuming and exchanging energy. These agents have an energy need, at each time step, that they must satisfy by consuming energy. However, they should respect a set of moral values as they do so, i.e., exhibiting an ethically-aligned behaviour.\nMoral values are encoded in the reward functions, which determine the \u0026ldquo;correctness\u0026rdquo; of an agent\u0026rsquo;s action, with respect to these moral values. Agents receive rewards as feedback that guide them towards a better behaviour.\n","date":"3 April 2023","externalUrl":null,"permalink":"/projects/ethical-smartgrid/","section":"Projects","summary":"Smart Grid simulator for Reinforcement Learning focusing on ethical behaviours.","title":"ethical-smart-grid","type":"projects"},{"content":"Learning behaviours aligned with moral values in a multi-agent system: guiding reinforcement learning with symbolic judgments\nThis is the manuscript and slides of my PhD Thesis in Computer Science, realized at the LIRIS lab, under the supervision of Professor Salima Hassas, Professor Olivier Boissier, and Dr. Mathieu Guillermin.\nThe thesis was defended at Université Claude Bernard Lyon 1 on 2022-10-27 before the following jury:\nPr. Parisa Ghodous \u0026ndash; Université Claude Bernard Lyon 1 \u0026ndash; President Dr. Grégory Bonnet \u0026ndash; Université de Caen Normandie \u0026ndash; Reviewer Pr. Marija Slavkovik \u0026ndash; University of Bergen \u0026ndash; Reviewer Dr. Alain Dutech \u0026ndash; INRIA Nancy \u0026ndash; Examiner Pr. Juan A. Rodríguez-Aguilar \u0026ndash; Autonomous University of Barcelona \u0026ndash; Examiner Pr. Salima Hassas \u0026ndash; Université Claude Bernard Lyon 1 \u0026ndash; Supervisor Pr. Olivier Boissier \u0026ndash; École des Mines de Saint-Étienne \u0026ndash; Co-supervisor Dr. Mathieu Guillermin \u0026ndash; Université Catholique de Lyon \u0026ndash; Co-supervisor ","date":"27 October 2022","externalUrl":null,"permalink":"/publication/phd_thesis/","section":"Research (Publications)","summary":"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).","title":"PhD Thesis","type":"publication"},{"content":"acronyms is the newest version of this library, made specifically for Quarto documents.\nIt works similarly to acronymsdown, which was designed as a Pandoc filter shipped in an R package for [R Markdown documents]. In the future, acronyms will have more features than acronymsdown.\nRmd and Quarto documents bring a simplified syntax over existing languages, such as LaTeX or HTML; however, no easy and integrated support for acronyms was available, as opposed to LaTeX\u0026rsquo;s glossaries package for example.\nThe typical workflow to use acronyms in a Rmd or Quarto document, without acronyms, would be to write in plain text the full name and its acronym, such as R Markdown (Rmd), the first time the acronym is used, then only the acronym on subsequent uses, such as Rmd. This involves remembering whether the acronym already appeared; if the first occurrence is changed or moved, the document might not be correct anymore.\nInstead, acronyms automates the use of acronyms, by first declaring them, and then using a special syntax throughout the document. The underlying filter will automatically replace each occurrence by the correct text, depending on whether it corresponds to the first use.\nUsing an acronym is as simple as writing:\n\\acr{Rmd} documents are great! \\acr{Rmd} relies on Pandoc internally. Each occurrence of \\acr{KEY} will be replaced, according to a user-configurable style, such as R Markdown (Rmd) or Rmd (R Markdown). In addition, a List of Acronym can be automatically generated, based on all defined acronyms.\nSee the GitHub page, the documentation for more details, or start using acronyms in your Quarto documents right away:\nquarto add rchaput/acronyms@master --- filters: - acronyms acronyms: keys: - shortname: Rmd longname: R Markdown --- ","date":"20 December 2021","externalUrl":null,"permalink":"/projects/acronymsdown/","section":"Projects","summary":"Adds support for acronyms in RMarkdown and Quarto documents.","title":"acronymsdown / acronyms","type":"projects"},{"content":"","date":"20 December 2021","externalUrl":null,"permalink":"/tags/computational-documents/","section":"Tags","summary":"","title":"Computational Documents","type":"tags"},{"content":"","date":"20 December 2021","externalUrl":null,"permalink":"/tags/lua/","section":"Tags","summary":"","title":"Lua","type":"tags"},{"content":"","date":"20 December 2021","externalUrl":null,"permalink":"/tags/quarto/","section":"Tags","summary":"","title":"Quarto","type":"tags"},{"content":"","date":"20 December 2021","externalUrl":null,"permalink":"/tags/r/","section":"Tags","summary":"","title":"R","type":"tags"},{"content":"In R, the default utils::capture.output function only redirects R messages: it does not truly redirect the system streams, and thus fails with sub-processes, such as pandoc when using RMarkdown.\nr2dup2 provides a way to truly redirect the error stream (stderr), by using the with_redirect_stderr function:\nr2dup2::with_redirect_stderr(file = \u0026#34;error.txt\u0026#34;, { system(\u0026#34;echo \u0026gt;\u0026amp;2 This line will be printed to error.txt\u0026#34;) }) r2dup2 is only available on GitHub, install it with the remotes package:\ninstall.packages(\u0026#34;remotes\u0026#34;) remotes::install_github(\u0026#34;rchaput/r2dup2\u0026#34;) ","date":"20 December 2021","externalUrl":null,"permalink":"/projects/r2dup2/","section":"Projects","summary":"Redirecting stderr messages in R","title":"r2dup2","type":"projects"},{"content":"","date":"20 December 2021","externalUrl":null,"permalink":"/tags/rmarkdown/","section":"Tags","summary":"","title":"Rmarkdown","type":"tags"},{"content":"","date":"23 September 2021","externalUrl":null,"permalink":"/authors/alain-mille/","section":"Authors","summary":"","title":"Alain Mille","type":"authors"},{"content":"","date":"23 September 2021","externalUrl":null,"permalink":"/authors/am%C3%A9lie-cordier/","section":"Authors","summary":"","title":"Amélie Cordier","type":"authors"},{"content":"","date":"23 September 2021","externalUrl":null,"permalink":"/publication/pfia2021/","section":"Research (Publications)","summary":"A technical report that served as a preparatory document for a tutorial that we\npresented at PFIA (French Platform on Artificial Intelligence) 2020, organized\nby the AFIA (French Association for Artificial Intelligence).","title":"An historical perspective on XAI","type":"publication"},{"content":"","date":"6 August 2021","externalUrl":null,"permalink":"/tags/drawio/","section":"Tags","summary":"","title":"Drawio","type":"tags"},{"content":"","date":"6 August 2021","externalUrl":null,"permalink":"/tags/knitr/","section":"Tags","summary":"","title":"Knitr","type":"tags"},{"content":"knitrdrawio is a publicly-available R package that brings a new engine to the knitr library, to automatically include draw.io diagrams in R Markdown documents (Rmd).\nRmd documents are powerful documents that increase reproducibility in research by integrating code chunks which are run when the document is processed by the knitr library and exported (e.g., to PDF or HTML webpages). Typical usages of such code chunks include, for example, the plotting of figures based on experiments data.\nHowever, no tool was easily accessible to include diagram images, especially those created by a third-party software, such as draw.io.\nBefore knitrdrawio, the alternative would have been to manually export the diagram from draw.io as an image (e.g., PNG, JPG, or PDF), and then to manually include it in the R Markdown document, as one would do with any Markdown document ([Image name](/path/to/image.png)).\nThis workflow is rather cumbersome and does not support the stakes of reproducibility, open science and reusability. Indeed, the export process, and its parameters, are separated from the rest of the document. One has to remember how to export the diagrams, from which source files, which are the correct versions, etc. Moreover, many scientists only include the exported images in their Version Control System (VCS), which makes it more difficult to modify the diagram later on (\u0026ldquo;where is that source file?!\u0026rdquo;).\nknitrdrawio was built to solve this, by extending the knitr library with a new chunk engine, which allows to seamlessly export and include draw.io diagrams.\nAutomatically exporting and including a diagram is as simple as writing:\n```{drawio my-super-diag1, src=\u0026#34;diag1.drawio\u0026#34;} ``` This code chunk is replaced by the actual image, automatically exported from the diag1.drawio diagram file, during the knitting process.\nOf course, parameters can be added to control the export process:\n```{drawio my-super-diag2, src=\u0026#34;diag2.drawio\u0026#34;, border=5, crop=FALSE, page.index=4} ``` Notice how the parameters are directly written in the document itself: any people trying to re-create your document (including future you!) will export the diagram exactly as you intended.\nAs a bonus, knitrdrawio builds upon knitr\u0026rsquo;s caching mechanism to avoid re-executing chunks if unnecessary. This means that, if you chose to enable cache, the chunk will be executed only once, as long as neither the parameters nor the diagram source file are changed.\nSee the GitHub page for more details, or start using knitrdrawio in your Rmd documents right away:\n```{r setup} install.packages(\u0026#34;remotes\u0026#34;) remotes::install_github(\u0026#34;rchaput/knitrdrawio\u0026#34;) library(knitrdrawio) ``` ","date":"6 August 2021","externalUrl":null,"permalink":"/projects/knitrdrawio/","section":"Projects","summary":"New engine for knitr that allows to include draw.io diagrams in R Markdown documents.","title":"knitrdrawio","type":"projects"},{"content":"","date":"6 August 2021","externalUrl":null,"permalink":"/tags/reproducibility/","section":"Tags","summary":"","title":"Reproducibility","type":"tags"},{"content":"","date":"29 June 2021","externalUrl":null,"permalink":"/publication/jfsma2021/","section":"Research (Publications)","summary":"Paper on the ability to use a symbolic reasoning approach to judge\nneural learning agents, in order to reward them appropriately with\nrespect to their ’ethical’ behavior, combining both approaches\nin a Hybrid method.","title":"Approche multi-agent combinant raisonnement et apprentissage pour un comportement éthique","type":"publication"},{"content":"","date":"29 June 2021","externalUrl":null,"permalink":"/tags/hybrid-neuro-symbolic-learning/","section":"Tags","summary":"","title":"Hybrid Neuro-Symbolic Learning","type":"tags"},{"content":"","date":"21 May 2021","externalUrl":null,"permalink":"/publication/aies2021/","section":"Research (Publications)","summary":"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.","title":"A Multi-Agent Approach to Combine Reasoning and Learning for an Ethical Behavior","type":"publication"},{"content":"","date":"8 February 2021","externalUrl":null,"permalink":"/tags/explainable-artificial-intelligence/","section":"Tags","summary":"","title":"Explainable Artificial Intelligence","type":"tags"},{"content":"","date":"8 February 2021","externalUrl":null,"permalink":"/publication/xai2021/","section":"Research (Publications)","summary":"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.","title":"Explanations: What does it mean for humans, for machines, for man-machines interactions?","type":"publication"},{"content":"","date":"8 February 2021","externalUrl":null,"permalink":"/tags/user-experience/","section":"Tags","summary":"","title":"User Experience","type":"tags"},{"content":"","date":"4 August 2020","externalUrl":null,"permalink":"/tags/linux/","section":"Tags","summary":"","title":"Linux","type":"tags"},{"content":"","date":"4 August 2020","externalUrl":null,"permalink":"/tags/py3status/","section":"Tags","summary":"","title":"Py3status","type":"tags"},{"content":"Py3status Random Wallpaper is a module for Py3status (which is itself a replacement for the default i3status in i3bar) that allows you to change your wallpaper. Each time the module is loaded (for example, when the i3bar is started), it will pick a random wallpaper amongst your library. You can also directly click on the module to change the wallpaper.\nThis module was made with high configurability in mind, and you can tweak several parameters, such as:\nthe folders which will be scanned for wallpapers; the buttons used to trigger a new change; the command used to set the wallpaper (by default, uses feh); an optional list of ignored files; and others\u0026hellip; ","date":"4 August 2020","externalUrl":null,"permalink":"/projects/py3status-wallpaper/","section":"Projects","summary":"py3status-random-wallpaper is a module for the Py3status bar, that allows you to easily change your wallpaper on GNU/Linux.","title":"Py3status Random Wallpaper","type":"projects"},{"content":"","date":"4 August 2020","externalUrl":null,"permalink":"/tags/xdg/","section":"Tags","summary":"","title":"XDG","type":"tags"},{"content":"XDG-Prefs is an Open-Source tool to manage your default applications on GNU/Linux, with a simple but efficient GUI.\nOn GNU/Linux systems, each file has a type, named the MIME Type (or Media Type), based on the XDG Specifications by Freedesktop. Your system maintains a database that specifies the default application you want to use for each MIME Type ; this database is available through the official xdg-mime tool, but the command-line interface is not suited for easy management (for example, you must remember the exact name of the MIME Type).\nXDG-Prefs offers a simple GUI that allows you to view and modify this database easily; it is built upon the same standard specifications, meaning that your preferences will be recognized by all other applications (typically, when you double-click on a file in your File Explorer).\nSuch a tool is commonly found in Desktop Environments, such as Gnome or KDE, but not in Window Managers, such as i3wm. XDG-Prefs is desktop-agnostic, meaning that you can use it on Gnome, KDE, or even i3.\n","date":"4 August 2020","externalUrl":null,"permalink":"/projects/xdgprefs/","section":"Projects","summary":"XDG-Prefs is an open-source tool to manage your default applications on GNU/Linux.","title":"XDG-Prefs","type":"projects"},{"content":"","date":"29 June 2020","externalUrl":null,"permalink":"/publication/jfsma20/","section":"Research (Publications)","summary":"Paper on adaptive learning of ethical behaviors I presented at JFSMA (French Days of Multi-Agent Systems).","title":"Apprentissage adaptatif de comportements éthiques","type":"publication"},{"content":"","date":"29 June 2020","externalUrl":null,"permalink":"/tags/energy-management/","section":"Tags","summary":"","title":"Energy Management","type":"tags"},{"content":" IA² is an Autumn school about Artificial Intelligence, organized by the GDR IA and financed by the CNRS. This 2019 edition of IA² was specialized on Smart Environment and Smart Cities, during which I presented a poster about my internship work on ethical behaviors of artificial agents and the application to intelligent distribution of energy inside a small Smart Grid.\nThe poster is in French\n","date":"1 October 2019","externalUrl":null,"permalink":"/publication/poster_gdria2019/","section":"Research (Publications)","summary":"Poster about my Master thesis, at an AI Autumn school.","title":"Poster at GDR IA 2019","type":"publication"},{"content":"","date":"1 October 2019","externalUrl":null,"permalink":"/tags/self-organizing-maps/","section":"Tags","summary":"","title":"Self-Organizing Maps","type":"tags"},{"content":"","date":"1 October 2019","externalUrl":null,"permalink":"/tags/smart-grids/","section":"Tags","summary":"","title":"Smart Grids","type":"tags"},{"content":" This is the thesis I wrote at the end of my Master in Artificial Intelligence. The subject was Evolutive learningof ethical behaviors, realized at the LIRIS lab, under the supervision of Professor Salima Hassas and Professor Olivier Boissier.\nThe documents (thesis and slides) are in French, but the English abstract is available.\n","date":"1 June 2019","externalUrl":null,"permalink":"/publication/master_thesis/","section":"Research (Publications)","summary":"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).","title":"Master Research Internship","type":"publication"},{"content":"","externalUrl":null,"permalink":"/aboutme/","section":"","summary":"","title":"About Me","type":"page"},{"content":"","externalUrl":"https://projet.liris.cnrs.fr/acceler-ai/","permalink":"/research/02_accelerai/","section":"Research Activities","summary":"","title":"Acceler-AI","type":"research"},{"content":"","externalUrl":null,"permalink":"/categories/","section":"Categories","summary":"","title":"Categories","type":"categories"},{"content":"","externalUrl":null,"permalink":"/tags/co-construction/","section":"Tags","summary":"","title":"Co-Construction","type":"tags"},{"content":"","externalUrl":null,"permalink":"/research/03_eciea/","section":"Research Activities","summary":"","title":"ECIÉA","type":"research"},{"content":"","externalUrl":"https://projet.liris.cnrs.fr/ethicsai/","permalink":"/research/01_ethicsai/","section":"Research Activities","summary":"","title":"Ethics.AI","type":"research"},{"content":"","externalUrl":null,"permalink":"/tags/explainability/","section":"Tags","summary":"","title":"Explainability","type":"tags"},{"content":"","externalUrl":null,"permalink":"/research/04_ia_sc/","section":"Research Activities","summary":"","title":"IAGen-StandardCells","type":"research"},{"content":"","externalUrl":null,"permalink":"/research/","section":"Research Activities","summary":"","title":"Research Activities","type":"research"},{"content":"","externalUrl":null,"permalink":"/series/","section":"Series","summary":"","title":"Series","type":"series"},{"content":"","externalUrl":null,"permalink":"/tags/standard-cell-conception/","section":"Tags","summary":"","title":"Standard Cell Conception","type":"tags"},{"content":"This page lists the course I currently teach. Most names and descriptions are in French for students.\n","externalUrl":null,"permalink":"/teaching/","section":"","summary":"","title":"Teaching","type":"page"}]