1. 2020
  2. Reinforcement Learning for the Optimization of Scouting Runs and Retention Modeling in Liquid Chromatography

    Kensert, A., Collaerts, G., Efthymiadis, K., Desmet, G. & Cabooter, D., Jan 2020.

    Research output: Unpublished contribution to conferencePoster

  3. A Utility-Based Analysis of Equilibria in Multi-Objective Normal Form Games

    Radulescu, R., Mannion, P., Zhang, Y., Roijers, D. & Nowe, A., 2020, In : The Knowledge Engineering Review. 35, 21 p., e32.

    Research output: Contribution to journalArticle

  4. An agent-based model of sign language persistence informed by real-world data

    Mudd, K., de Vos, C. & De Boer, B., 2020, (Accepted/In press) In : Language dynamics and change.

    Research output: Contribution to journalArticle

  5. An Interpretable Semi-supervised Classifier using Rough Sets for Amended Self-labeling

    Grau, I., Sengupta, D., Garcia Lorenzo, M. M. & Nowe, A., 2020, Proceedings of the 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, p. 1-8

    Research output: Chapter in Book/Report/Conference proceedingConference paper

  6. Deep reinforcement learning for large-scale epidemic control

    Libin, P., Moonens, A., Verstraeten, T., Perez Sanjines, F. R., Hens, N., Lemey, P. & Nowe, A., 2020, (Accepted/In press) Proceedings of the Adaptive and Learning Agents Workshop 2020 (ALA2020) at AAMAS. 9 p.

    Research output: Chapter in Book/Report/Conference proceedingConference paper

  7. Evolutionary Dynamics Do Not Motivate a Single-Mutant Theory of Human Language

    De Boer, B., Thompson, B., Ravignani, A. & Boeckx, C., 2020, In : Scientific Reports. 10, 451, p. 1-9 9 p., 451.

    Research output: Contribution to journalArticle

  8. Executable First-Order Queries in the Logic of Information Flows

    Aamer, H., Bogaerts, B., SURINX, D., Ternovska, E. & Van den Bussche, J., 2020, 23rd International Conference on Database Theory (ICDT 2020). Lutz, C. & Jung, C. (eds.). Vol. 155. p. 4:1-4:14 14 p. (Leibniz International Proceedings in Informatics (LIPIcs); vol. 155).

    Research output: Chapter in Book/Report/Conference proceedingConference paper

  9. Multi-Agent Reinforcement Learning Tool for Job Shop Scheduling Problems

    Jiménez, Y. M., Palacio, J. C. & Nowé, A., 2020, Optimization and Learning - Third International Conference, OLA2020, Cádiz, Spain, February 17-19, 2020, Proceedings. Dorronsoro, B., Ruiz, P., Torre, J. C. D. L., Urda, D. & Talbi, E-G. (eds.). Springer, Vol. 1173. p. 3-12 10 p. (Communications in Computer and Information Science).

    Research output: Chapter in Book/Report/Conference proceedingConference paper

  10. Multi-Objective Multi-Agent Decision Making: A Utility-based Analysis and Survey: JAAMAS Track

    Radulescu, R., Mannion, P., Roijers, D. & Nowe, A., 2020, Proceedings of the 19th International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2020 . IFAAMAS, p. 2158-2160

    Research output: Chapter in Book/Report/Conference proceedingConference paper

  11. Opponent Modelling for Reinforcement Learning in Multi-Objective Normal Form Games: Extended Abstract

    Zhang, Y., Radulescu, R., Mannion, P., Roijers, D. & Nowe, A., 2020, Proceedings of the 19th International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2020. IFAAMAS, p. 2080-2082

    Research output: Chapter in Book/Report/Conference proceedingConference paper

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