Arthur Guijt, Ngoc Hoang Luong, Peter A.N. Bosman, Mathijs de Weerdt (2022), On the impact of linkage learning, gene-pool optimal mixing, and non-redundant encoding on permutation optimization, In Swarm and Evolutionary Computation Volume 70.

G. Veviurko, J.W. Böhmer, Laurens Mackay, M.M. de Weerdt (2022), Surrogate DC Microgrid Models for Optimization of Charging Electric Vehicles under Partial Observability, In Energies Volume 15.

Ksenija Stepanovic, Jichen Wu, Rob Everhardt, Mathijs de Weerdt (2022), Unlocking the Flexibility of District Heating Pipeline Energy Storage with Reinforcement Learning, In Energies Volume 15 p.1-25.

K. Stepanovic, Jichen Wu, Rob Everhardt, M.M. de Weerdt (2022), Unlocking the Flexibility of District Heating Pipeline Energy Storage with Reinforcement Learning, 34th Benelux Conference on Artificial Intelligence (BNAIC) and the 30th Belgian Dutch Conference on Machine Learning (Benelearn).

Pallas Agterberg, Maarten Bijl, J. L. Hurink, J.A. la Poutré, Gerdien van de Vreede, M.M. de Weerdt, Tijs Wilbrink (2021), AI as an accelerator of the energy transitition: Opportunities for a carbon-free energy system.

Koos van der Linden, Natalia Romero, Mathijs de Weerdt (2021), Benchmarking Flexible Electric Loads Scheduling Algorithms, In Energies Volume 14 p.1-16.

Laurens Bliek, Arthur Guijt, Sicco Verwer, Mathijs De Weerdt (2021), Black-box mixed-variable optimisation using a surrogate model that satisfies integer constraints, In GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion p.1851-1859, Association for Computing Machinery (ACM).

Frits de Nijs, Erwin Walraven, Mathijs M. de Weerdt, Matthijs T.J. Spaan (2021), Constrained multiagent Markov decision processes: A taxonomy of problems and algorithms, In Journal of Artificial Intelligence Research Volume 70 p.955-1001.

Rickard Karlsson, Laurens Bliek, Sicco Verwer, Mathijs de Weerdt (2021), Continuous Surrogate-Based Optimization Algorithms Are Well-Suited for Expensive Discrete Problems, Mitra Baratchi, Lu Cao, Walter A. Kosters, Jefrey Lijffijt, Jan N. van Rijn, Frank W. Takes (Eds.), In Artificial Intelligence and Machine Learning - 32nd Benelux Conference, BNAIC/Benelearn 2020, Revised Selected Papers p.48-63, Springer.

Anna Stawska, Natalia Romero Lane, Mathijs de Weerdt, Remco Verzijlbergh (2021), Demand response: For congestion management or for grid balancing?, In Energy Policy Volume 148.