Q. Yang, M.T.J. Spaan (2023), CEM: Constrained Entropy Maximization for Task-Agnostic Safe Exploration, In The Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23).
Danial Kamran, Thiago D. Simão, Qisong Yang, Canmanie T. Ponnambalam, Johannes Fischer, Matthijs T.J. Spaan, Martin Lauer (2022), A Modern Perspective on Safe Automated Driving for Different Traffic Dynamics using Constrained Reinforcement Learning, In Proceedings of the IEEE International Conference on Intelligent Transportation Systems p.4017-4023, IEEE .
Sebastian Junges, Matthijs T.J. Spaan (2022), Abstraction-Refinement for Hierarchical Probabilistic Models, Sharon Shoham, Yakir Vizel (Eds.), In Computer Aided Verification - 34th International Conference, CAV 2022, Proceedings p.102-123, Springer Science+Business Media.
Johan Los, Frederik Schulte, Matthijs T.J. Spaan, Rudy R. Negenborn (2022), An Auction-Based Multi-Agent System for the Pickup and Delivery Problem with Autonomous Vehicles and Alternative Locations, Michael Freitag, Aseem Kinra, Herbert Kotzab, Nicole Megow (Eds.), In Dynamics in Logistics p.244-260, Springer Science+Business Media.
Canmanie Ponnambalam, Danial Kamran, Thiago D. Simão, Frans A. Oliehoek, Matthijs T.J. Spaan (2022), Back to the Future: Solving Hidden Parameter MDPs with Hindsight.
Miguel Suau, Jinke He, Matthijs T.J. Spaan, Frans A. Oliehoek (2022), Influence-Augmented Local Simulators: a Scalable Solution for Fast Deep RL in Large Networked Systems, K. Chaudhuri, S. Jegelka, L. Song, C. Szepesvari, G. Niu, S. Sabato (Eds.), In Proceedings of the 39th International Conference on Machine Learning Volume 162 p.20604-20624, PMLR.
Johan Los, Frederik Schulte, Margaretha Gansterer, Richard F. Hartl, Matthijs T.J. Spaan, Rudy R. Negenborn (2022), Large-scale collaborative vehicle routing, In Annals of Operations Research.
Katia Sycara, Vasant Honavar, M.T.J. Spaan (Eds.) (2022), Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence (AAAI).
Q. Yang, T. D. Simão, Simon H. Tindemans, M.T.J. Spaan (2022), Refined Risk Management in Safe Reinforcement Learning with a Distributional Safety Critic, David Bossens, Stephen Giguere, Roderick Bloem, Bettina Koenighofer (Eds.), In Safe RL Workshop at IJCAI 2022.
Qisong Yang, Thiago D Simão, Simon H. Tindemans, Matthijs T.J. Spaan (2022), Safety-constrained reinforcement learning with a distributional safety critic, In Machine Learning Volume 112 p.859-887.