1. 2020
  2. Multi-Agent Thompson Sampling for Bandits with Sparse Neighbourhood Structures

    Verstraeten, T., Bargiacchi, E., Libin, P., Helsen, J., Roijers, D. M. & Nowe, A., 19 Nov 2020, Proceedings of the 32nd Benelux Conference on Artificial Intelligence (BNAIC 2020). Cao, L., Kosters, W. & Lijffijt, J. (eds.). CEUR Workshop Proceedings, p. 394-395 2 p.

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

  3. Fleet Control using Coregionalized Gaussian Process Policy Iteration

    Verstraeten, T., Libin, P. & Nowe, A., 8 Jun 2020, Proceedings of the 24th European Conference on Artificial Intelligence (ECAI 2020). IOS Press, p. 1571-1578 8 p.

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

  4. Thompson Sampling for Factored Multi-Agent Bandits

    Verstraeten, T., Bargiacchi, E., Libin, P., Roijers, D. & Nowe, A., 31 May 2020, Proceedings of the 19th International Conference on Autonomous Agents and Multi-Agent Systems. IFAAMAS, 2 p.

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

  5. Thompson Sampling for Loosely-Coupled Multi-Agent Systems: An Application to Wind Farm Control

    Verstraeten, T., Bargiacchi, E., Libin, P., Roijers, D. & Nowe, A., 9 May 2020. 9 p.

    Research output: Unpublished contribution to conferenceUnpublished paper

  6. Multi-Agent Thompson Sampling for Bandit Applications with Sparse Neighbourhood Structures

    Verstraeten, T., Bargiacchi, E., Libin, P., Helsen, J., Roijers, D. & Nowe, A., 21 Apr 2020, In : Scientific Reports - Nature. 10, 1, 14 p., 6728.

    Research output: Contribution to journalArticle

  7. 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

  8. Fleet oriented pattern mining combined with time series signature extraction for understanding of wind farm response to storm conditions

    Daems, P-J., Feremans, L., Verstraeten, T., Cule, B., Goethals, B. & Helsen, J., 2020, World conference for condition monitoring. 2 ed. Springer, p. 275-287 12 p.

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

  9. 2019
  10. Failure Avoidance for Wind Turbines through Fleetwide Control

    Verstraeten, T., Nowe, A. & Helsen, J., 6 Nov 2019, Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019). CEUR Workshop Proceedings, Vol. 2491. 2 p.

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

  11. Privacy preserving reinforcement learning over distributed datasets

    Loeb, R., Verstraeten, T., Nowe, A. & Dooms, A., 6 Nov 2019, BNAIC: Belgium-Netherlands Conference on Artificial Intelligence. Vol. 2491. 153783. (CEUR Workshop Proceedings).

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

  12. Bayesian Anytime m-top Exploration

    Libin, P., Verstraeten, T., Roijers, D. M., Wang, W., Theys, K. & Nowe, A., Nov 2019, 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI). p. 1422-1428 7 p.

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

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