Erwin Walraven

This webpage contains information about my publications and software. More recent information can be found on Google Scholar and LinkedIn.

Publications

Information gathering in POMDPs using active inference Erwin Walraven, Joris Sijs and Gertjan J. Burghouts Autonomous Agents and Multi-Agent Systems, vol. 39, 2025.
The Dial-a-Ride problem with meeting points: A problem formulation for shared demand–responsive transit Lianne Cortenbach, Konstantinos Gkiotsalitis, Eric van Berkum and Erwin Walraven Transportation Research Part C: Emerging Technologies, vol. 169, 104869, 2024.
Open-World Visual Reasoning by a Neuro-Symbolic Program of Zero-Shot Symbols Gertjan Burghouts, Fieke Hillerström, Erwin Walraven, Michael van Bekkum, Frank Ruis, Joris Sijs, Jelle van Mil and Judith Dijk International Conference on Pattern Recognition and Artificial Intelligence, 2024.
Parking in Macroscopic Transport Models: Modelling Parking Capacities in Traffic Assignment Dawn Spruijtenburg, Erwin Walraven, Reinier Sterkenburg and Marieke van der Tuin Transport Research Arena (TRA), 2024.
PERFEX: Classifier Performance Explanations for Trustworthy AI Systems Erwin Walraven, Ajaya Adhikari and Cor J. Veenman Proceedings of the World Conference on Explainable Artificial Intelligence, pp. 164-180, 2023.
Building digital twins of cities using the Inter Model Broker framework Walter Lohman, Hans Cornelissen, Jeroen Borst, Ralph Klerkx, Yashar Araghi and Erwin Walraven Future Generation Computer Systems, vol. 148, pp. 501-513, 2023.
Simultaneous modelling of access, egress & transit line choice for public transport Marieke van der Tuin, Han Zhou and Erwin Walraven Transportation Research Procedia, vol. 72, pp. 3793-3800, 2023.
The Short-Term Potential of Artificial Intelligence for Traffic Management Henk Taale, Erwin Walraven, Dawn Spruijtenburg and Isabel Wilmink European Transport Conference, 2022.
Anomaly Detection in an Open World by a Neuro-symbolic Program on Zero-shot Symbols Gertjan J. Burghouts, Fieke Hillerström, Erwin Walraven, Michael van Bekkum, Frank Ruis and Joris Sijs IROS 2022 Workshop Probabilistic Robotics in the Age of Deep Learning, 2022.
Constrained Multiagent Markov Decision Processes: a Taxonomy of Problems and Algorithms Frits de Nijs, Erwin Walraven, Mathijs de Weerdt and Matthijs T. J. Spaan Journal of Artificial Intelligence Research, vol. 70, pp. 955-1001, 2021.
Point-Based Value Iteration for Finite-Horizon POMDPs Erwin Walraven and Matthijs T. J. Spaan Journal of Artificial Intelligence Research, vol. 65, pp. 307–341, 2019.
Planning under Uncertainty in Constrained and Partially Observable Environments PhD dissertation, Delft University of Technology, 2019.
Column Generation Algorithms for Constrained POMDPs Erwin Walraven and Matthijs T. J. Spaan Journal of Artificial Intelligence Research, vol. 62, pp. 489–533, 2018.
Bootstrapping LPs in Value Iteration for Multi-Objective and Partially Observable MDPs Diederik M. Roijers, Erwin Walraven and Matthijs T. J. Spaan Proceedings of the 28th Int. Conference on Automated Planning and Scheduling, pp. 218–226, 2018.
Accelerated Vector Pruning for Optimal POMDP Solvers (supplement) Erwin Walraven and Matthijs T. J. Spaan Proceedings of the 31st AAAI Conference on Artificial Intelligence, pp. 3672–3678, 2017.
Bounding the Probability of Resource Constraint Violations in Multi-Agent MDPs (supplement) Frits de Nijs, Erwin Walraven, Mathijs M. de Weerdt and Matthijs T. J. Spaan Proceedings of the 31st AAAI Conference on Artificial Intelligence, pp. 3562–3568, 2017.
Planning Under Uncertainty for Aggregated Electric Vehicle Charging with Renewable Energy Supply Erwin Walraven and Matthijs T. J. Spaan Proceedings of the 22nd European Conference on Artificial Intelligence, pp. 904–912, 2016.
Traffic flow optimization: A reinforcement learning approach Erwin Walraven, Matthijs T. J. Spaan and Bram Bakker Engineering Applications of Artificial Intelligence, vol. 52, pp. 203–212, 2016.
Planning under Uncertainty for Aggregated Electric Vehicle Charging using Markov Decision Processes Erwin Walraven and Matthijs T. J. Spaan International Workshop on Artificial Intelligence for Smart Grids and Smart Buildings, 2016.
Planning under Uncertainty with Weighted State Scenarios Erwin Walraven and Matthijs T. J. Spaan Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence, pp. 912–921, 2015.
A Scenario State Representation for Scheduling Deferrable Loads under Wind Uncertainty Erwin Walraven and Matthijs T. J. Spaan The 10th Annual Workshop on Multiagent Sequential Decision Making Under Uncertainty, 2015.
Traffic Flow Optimization using Reinforcement Learning (abstract) Proceedings of the 26th Benelux Conference on Artificial Intelligence, pp. 211–212, 2014.
Traffic Flow Optimization using Reinforcement Learning Master's thesis, Delft University of Technology, 2014.
Enhancing SAT Based Planning with Landmark Knowledge Jan Elffers, Dyan Konijnenberg, Erwin Walraven and Matthijs T. J. Spaan Proceedings of the 25th Benelux Conference on Artificial Intelligence, pp. 64–71, 2013.

Software

My accelerated version of incremental pruning for POMDPs is available in SolvePOMDP, which is an open source software toolbox containing exact and approximate algorithms for POMDPs.

The ConstrainedPlanningToolbox contains a collection of algorithms for constrained multi-agent planning under uncertainty.

The finite-horizon POMDP solver FiVI is not available as stand-alone implementation, but the source code is part of the ConstrainedPlanningToolbox. It can be found in this file.

The source code of PERFEX and my implementation of active inference are available on GitHub.

Publications

Accelerated Vector Pruning for Optimal POMDP Solvers (supplement)

Bounding the Probability of Resource Constraint Violations in Multi-Agent MDPs (supplement)

Traffic Flow Optimization using Reinforcement Learning

Software