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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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About me
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Here is a nerdy shower thought, this one is certainly going to be a bit boring for the commoners, sorry mates!
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Life is made up of compromises.
Edith Warton
Short description of portfolio item number 1
Short description of portfolio item number 2
Published in Proceedings of the 14th International Conference on Agents and Artificial Intelligence, 2022
Nominated for best student paper award.
Recommended citation: Felten, F., Danoy, G., Talbi, E. and Bouvry, P. (2022). Metaheuristics-based Exploration Strategies for Multi-Objective Reinforcement Learning. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-547-0; ISSN 2184-433X, pages 662-673. DOI: 10.5220/0010989100003116. https://www.scitepress.org/Link.aspx?doi=10.5220/0010989100003116
Published in International Conference in Optimization and Learning (OLA2022), 2022
Applying decomposition techniques from MOO to MORL.
Recommended citation: F. Felten, E.-G. Talbi, and G. Danoy, (2022). MORL/D: Multi-Objective Reinforcement Learning based on Decomposition. In Proceedings of International Conference on Optimization and Learning (OLA2022) https://ola2022.sciencesconf.org/data/pages/Proceedings_1.pdf
Published in BNAIC/BeNeLearn 22, 2022
Open source library for Multi-Objective RL.
Recommended citation: L. N. Alegre, F. Felten, E.-G. Talbi, G. Danoy, A. Nowé, and A. L. C. Bazzan, “MO-Gym: A Library of Multi-Objective Reinforcement Learning Environments,” Proceedings of the 34th Benelux Conference on Artificial Intelligence BNAIC/Benelearn 2022 https://bnaic2022.uantwerpen.be/wp-content/uploads/BNAICBeNeLearn_2022_submission_6485.pdf
Published in Multi-Objective Decision Making Workshop (MODeM2023), 2023
Setting up the foundations for HPO 4 MORL.
Recommended citation: F. Felten, D. Gareev, E.-G. Talbi, and G. Danoy, (2023). Hyperparameter Optimization for Multi-Objective Reinforcement Learning. arXiv, Oct. 25, 2023. doi: 10.48550/arXiv.2310.16487. https://arxiv.org/abs/2310.16487
Published in Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track, 2023
MO-Gymnasium + MORL-baselines + Public datasets of training results.
Recommended citation: Florian Felten, Lucas Nunes Alegre, Ann Nowe, Ana L. C. Bazzan, El Ghazali Talbi, Grégoire Danoy, and Bruno Castro da Silva, ‘A Toolkit for Reliable Benchmarking and Research in Multi-Objective Reinforcement Learning’, in Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS 2023). https://openreview.net/forum?id=jfwRLudQyj
Published in Journal of Artificial Intelligence Research (JAIR), 2024
MOO/D + RL = MORL/D
Recommended citation: Florian Felten, El Ghazali Talbi, and Grégoire Danoy, ‘Multi-Objective Reinforcement Learning Based on Decomposition: A Taxonomy and Framework’, in Journal of Artificial Intelligence Research. https://www.jair.org/index.php/jair/article/view/15702
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Presentation of Metaheuristics-based Exploration Strategies for Multi-Objective Reinforcement Learning at ICAART.
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My research explained in less than 2 minutes.
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Recording of my talk at the MODeM workshop at ECAI 2023.
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Research on drones in Luxembourg explained to the national journal: https://www.rtl.lu/news/national/a/2198613.html.
Undergraduate course, University of Luxembourg, Department of Computer Science, 2022
In this course co-teached with Pierre Talbot, we aim to introduce CS students to various programming paradigms. The first part, mainly given by Pierre, focuses on Functional Programming. My part focuses on concurrent programming.