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M. Suau, M.T.J. Spaan, F.A. Oliehoek (2023), Bad Habits: Policy Confounding and Out-of-Trajectory Generalization in RL, In European Reinforcement Learning Workshop.

Laurens Bliek, Arthur Guijt, Rickard Karlsson, Sicco Verwer, Mathijs de Weerdt (2023), Benchmarking surrogate-based optimisation algorithms on expensive black-box functions, In Applied Soft Computing Volume 147.

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Anna Lukina (2023), Combining Runtime Monitoring and Machine Learning with Human Feedback, Brian Williams, Yiling Chen, Jennifer Neville (Eds.), In AAAI-23 Special Programs, IAAI-23, EAAI-23, Student Papers and Demonstrations p.15448-15448, American Association for Artificial Intelligence (AAAI).

Ali Nadi, Neil Yorke-Smith, Maaike Snelder, J. W.C. Van Lint, Lóránt Tavasszy (2023), Data-driven preference-based routing and scheduling for activity-based freight transport modelling, In Transportation Research Part C: Emerging Technologies Volume 158.

Dirk van Bokkem, Max van den Hemel, Sebastijan Dumančić, Neil Yorke-Smith (2023), Embedding a Long Short-Term Memory Network in a Constraint Programming Framework for Tomato Greenhouse Optimisation, Brian Williams, Yiling Chen, Jennifer Neville (Eds.), In AAAI-23 Special Programs, IAAI-23, EAAI-23, Student Papers and Demonstrations p.15731-15737, American Association for Artificial Intelligence (AAAI).

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Roland Saur, Han La Poutré, Neil Yorke-Smith (2023), Fair Pricing for Time-Flexible Smart Energy Markets, In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS p.2703-2705.

Isaak L. Geursen, Bruno F. Santos, N. Yorke-Smith (2023), Fleet planning under demand and fuel price uncertainty using actor–critic reinforcement learning, In Journal of Air Transport Management Volume 109.