Publications

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Classified by Publication Type

• Journal • Book • Book Chapter • Refereed Conference (International) • Refereed Conference (Local) • Refereed Workshop • Technical Report • arXiv • Ph.D. Thesis • Master's Thesis • Other • Unspecified •

Journal

1. Roberto Rocchetta, Alexander Mey, and Frans A. Oliehoek. A Survey on Scenario Theory, Complexity, and Compression-Based Learning and Generalization. IEEE Transactions on Neural Networks and Learning Systems, ():1–15, 2023.
   Details     Download: pdf [3.2MB]  ps.gz ps HTML 
2. Rolf A. N. Starre, Marco Loog, Elena Congeduti, and Frans A Oliehoek. An Analysis of Model-Based Reinforcement Learning From Abstracted Observations. Transactions on Machine Learning Research, 2023.
   Details     Download: pdf [795.5kB]  
3. Shi Yuan Tang, Athirai A. Irissappane, Frans A. Oliehoek, and Jie Zhang. Teacher-apprentices RL (TARL): leveraging complex policy distribution through generative adversarial hypernetwork in reinforcement learning. Autonomous Agents and Multi-Agent Systems, 37(2):25, 2023.
   Details     Download: pdf ps.gz ps HTML 
4. Jacopo Castellini, Sam Devlin, Frans A. Oliehoek, and Rahul Savani. Difference Rewards Policy Gradients. Neural Computing and Applications, November 2022. Postproceedings of ALA'21 workshop, where the paper won the best paper award.
   Details     Download: pdf [16.0MB]  ps.gz ps HTML 
5. Miguel Suau, Jinke He, Elena Congeduti, Rolf A.N. Starre, Aleksander Czechowski, and Frans A. Oliehoek. Influence-aware memory architectures for deep reinforcement learning in POMDPs. Neural Computing and Applications, September 2022.
   Details     Download: pdf [3.1MB]  ps.gz ps HTML 
6. Jacopo Castellini, Frans A. Oliehoek, Rahul Savani, and Shimon Whiteson. Analysing factorizations of action-value networks for cooperative multi-agent reinforcement learning. Autonomous Agents and Multi-Agent Systems, 35(25), June 2021.
   Details     Download: pdf [3.2MB]  ps.gz ps HTML 
7. Christian Neumeyer, Frans A. Oliehoek, and Dariu Gavrila. General-Sum Multi-Agent Continuous Inverse Optimal Control. IEEE Robotics and Automation Letters, 6(2):3429–3436, IEEE, 2021.
   Details     Download: pdf [386.6kB]  ps.gz ps HTML 
8. Frans A. Oliehoek, Stefan Witwicki, and Leslie P. Kaelbling. A Sufficient Statistic for Influence in Structured Multiagent Environments. Journal of Artificial Intelligence Research, pp. 789–870, AI Access Foundation, Inc., February 2021.
   Details     Download: pdf [3.3MB]  ps.gz ps HTML 
9. Zeynep Akata, Dan Balliet, Maarten de Rijke, Frank Dignum, Virginia Dignum, Guszti Eiben, Antske Fokkens, Davide Grossi, Koen Hindriks, Holger Hoos, Haley Hung, Catholijn Jonker, Christof Monz, Mark Neerincx, Frans Oliehoek, Henri Prakken, Stefan Schlobach, Linda van der Gaag, Frank van Harmelen, Herke van Hoof, Birna van Riemsdijk, Aimee van Wynsberghe, Rineke Verbrugge, Bart Verheij, Piek Vossen, and Max Welling. A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence. Computer, 53(08):18–28, August 2020. Best Paper Award for Computer Journal 2020
   Copyright by IEEE. Also see the publisher's version.
   Details     Download: pdf [421.6kB]  ps.gz ps HTML 
10. Christopher Amato, Haitham Bou Ammar, Elizabeth Churchill, Erez Karpas, Takashi Kido, Mike Kuniavsky, WF Lawless, Frans A Oliehoek, Francesca Rossi, Stephen Russell, Keiki Takadama, Siddharth Srivastava, Philip Karl Tuyls abd Van Allen, K. Brent Venable, Peter Vrancx, and Shiqi Zhang . Reports of the 2018 AAAI Spring Symposium Series. AI Magazine, 39(4):29–, 2018.
    Details     Download: pdf ps.gz ps HTML 
11. Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek, and Matthijs T. J. Spaan. Exploiting submodular value functions for scaling up active perception. Autonomous Robots, 42(2):209–233, February 2018.
    Details     Download: pdf [1.6MB]  ps.gz ps HTML 
12. Frans A. Oliehoek, Matthijs T. J. Spaan, Bas Terwijn, Philipp Robbel, and João V. Messias. The MADP Toolbox: An Open Source Library for Planning and Learning in (Multi-)Agent Systems. Journal of Machine Learning Research, 18(89):1–5, 2017.
    Details     Download: pdf [291.4kB]  
13. Nisar Ahmed, Paul Bello, Selmer Bringsjord, Micah Clark, Bradley Hayes, Andrey Kolobov, Christopher Miller, Frans Oliehoek, Frank Stein, and Matthijs Spaan. The 2015 AAAI Fall Symposium Series Reports. AI Magazine, 37(2):85–90, 2016.
    Details     Download: HTML 
14. Christopher Amato, Ofra Amir, Joanna Bryson, Barbara Grosz, Bipin Indurkhya, Emre Kiciman, Takashi Kido, W. F. Lawless, Miao Liu, Braden McDorman, Ross Mead, Frans A. Oliehoek, Andrew Specian, Georgi Stojanov, and Keiki Takadama. Reports of the AAAI 2016 Spring Symposium Series. AI Magazine, 37(4):83–88, 2016.
    Details     Download: HTML 
15. Diederik M. Roijers, Shimon Whiteson, and Frans A. Oliehoek. Computing Convex Coverage Sets for Faster Multi-Objective Coordination. Journal of Artificial Intelligence Research, 52:399–443, AI Access Foundation, Inc., March 2015.
    Details     Download: pdf [951.4kB]  ps.gz ps HTML 
16. Frans A. Oliehoek, Matthijs T. J. Spaan, Christopher Amato, and Shimon Whiteson. Incremental Clustering and Expansion for Faster Optimal Planning in Decentralized POMDPs. Journal of Artificial Intelligence Research, 46:449–509, 2013.
    Details     Download: pdf [7.2MB]  ps.gz ps [2.2MB]  HTML 
17. Frans A. Oliehoek, Julian F. P. Kooij, and Nikos Vlassis. The Cross-Entropy Method for Policy Search in Decentralized POMDPs. Informatica, 32:341–357, 2008.
    Details     Download: pdf [322.2kB]  
18. Frans A. Oliehoek, Matthijs T. J. Spaan, and Nikos Vlassis. Optimal and Approximate Q-value Functions for Decentralized POMDPs. Journal of Artificial Intelligence Research, 32:289–353, 2008.
    Details     Download: pdf [613.0kB]  ps.gz [403.8kB]  ps HTML 

Book

1. Frans A. Oliehoek and Christopher Amato. A Concise Introduction to Decentralized POMDPs, SpringerBriefs in Intelligent Systems, Springer, May 2016.
   Authors' pre-print. Final version availabe at Springer.
   Details     Download: pdf [3.0MB]  ps.gz ps HTML 

Book Chapter

1. Julia Efremova, Bijan Ranjbar-Sahraei, Hossein Rahmani, Frans A. Oliehoek, Toon Calders, Karl Tuyls, and Gerhard Weiss. Multi-Source Entity Resolution for Genealogical Data. In Gerrit Bloothooft, Peter Christen, Kees Mandemakers, and Marijn Schraagen, editors, Population Reconstruction, pp. 129–154, Springer International Publishing, July 2015.
   Details     Download: pdf [1004.5kB]  ps.gz ps HTML 
2. Frans A. Oliehoek. Decentralized POMDPs. In Marco Wiering and Martijn van Otterlo, editors, Reinforcement Learning: State of the Art, Adaptation, Learning, and Optimization, pp. 471–503, Springer, Berlin, Germany, 2012.
   Details     Download: pdf [3.0MB]  ps.gz ps HTML 
3. Frans A. Oliehoek and Arnoud Visser. A Decision-Theoretic Approach to Collaboration: Principal Description Methods and Efficient Heuristic Approximation. In Robert Babu\vska and Frans C. A. Groen, editors, Interactive Collaborative Information Systems, Studies in Computational Intelligence, pp. 87–124, Springer Berlin Heidelberg, Berlin, Germany, 2010.
   Details     Download: pdf [4.8MB]  ps.gz ps HTML 

Refereed Conference (International)

1. Raphaël Avalos, Eugenio Bargiacchi, Ann Nowe, Diederik Roijers, and Frans A Oliehoek. Online Planning in POMDPs with State-Requests. In Proceedings of the First International Conference on Reinforcement Learning (RLC), August 2024.
   Details     Download: pdf [658.5kB]  
2. Ariyan Bighashdel, Yongzhao Wang, Stephen McAleer, Rahul Savani, and Frans A. Oliehoek. Policy Space Response Oracles: A Survey. In Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI), International Joint Conferences on Artificial Intelligence Organization, August 2024. Survey Track
   Details     Download: pdf [301.6kB]  
3. Robert Loftin, Mustafa Mert Çelikok, Herke van Hoof, Samuel Kaski, and Frans A Oliehoek. Uncoupled Learning of Differential Stackelberg Equilibria with Commitments. In Proceedings of the Twenty-Third International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2024.
   Details     Download: pdf [585.1kB]  
4. Miguel Suau, Matthijs T. J. Spaan, and Frans A. Oliehoek. Bad Habits: Policy Confounding and Out-of-Trajectory Generalization in RL. In Proceedings of the First International Conference on Reinforcement Learning (RLC), August 2024. Outstanding Paper Award on Scientific Understanding in RL
   Details     Download: pdf [993.1kB]  
5. Jinke He, Thomas M. Moerland, Joery A. De Vries, and Frans A. Oliehoek. What model does MuZero learn?. In ECAI 2024 - 27th European Conference on Artificial Intelligence (ECAI), pp. 1599–1606, October 2024.
   Details     Download: pdf [1.5MB]  ps.gz ps HTML 
6. Kata Naszadi, Frans A. Oliehoek, and Christof Monz. Communicating with Speakers and Listeners of Different Pragmatic Levels. In Conference on Empirical Methods in Natural Language Processing (EMNLP), October 2024.
   Details     Download: pdf [577.9kB]  
7. Aleksander Czechowski and Frans A. Oliehoek. Safety Guarantees in Multi-agent Learning via Trapping Regions. In Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI), August 2023.
   Details     Download: pdf [406.7kB]  
8. Aleksander Czechowski and Frans A. Oliehoek. Safety Guarantees in Multi-agent Learning via Trapping Regions (Extended Abstract). In Proceedings of the Twenty-Second International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2023.
   Details     Download: pdf [606.6kB]  
9. Zuzanna Osika, Jazmin Zatarain-Salazar, Diederik M. Roijers, Oliehoek Frans A., and Murukannaiah Pradeep K.. What Lies beyond the Pareto Front? A Survey on Decision-Support Methods for Multi-Objective Optimization. In Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI), August 2023.
   Details     Download: pdf [2.7MB]  
10. Mustafa Mert Çelikok, Frans A. Oliehoek, and Samuel Kaski. Best-Response Bayesian Reinforcement Learning with BA-POMDPs for Centaurs. In Proceedings of the Twenty-First International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 235–243, May 2022.
    Details     Download: pdf [1.2MB]  
11. Sammie Katt, Hai Nguyen, Frans A. Oliehoek, and Christopher Amato. BADDr: Bayes-Adaptive Deep Dropout RL for POMDPs. In Proceedings of the Twenty-First International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2022.
    Details     Download: pdf [4.2MB]  
12. Vibhav Kedege, Aleksander Czechowski, Ludo Stellingwerff, and Frans A. Oliehoek. Multi Robot Surveillance and Planning in Limited Communication Environments. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,, pp. 139–147, SciTePress, 2022.
    The published version of this paper can be found at https://www.scitepress.org/Papers/2022/107755/
    Details     Download: pdf [771.9kB]  ps.gz ps HTML 
13. Robert Loftin and Frans A Oliehoek. On the Impossibility of Learning to Cooperate with Adaptive Partner Strategies in Repeated Games. In Proceedings of the 39th International Conference on Machine Learning (ICML), pp. 14197–14209, 2022.
    Details     Download: pdf [280.8kB]  
14. Markus Peschl, Arkady Zgonnikov, Frans A. Oliehoek, and Luciano Siebert. MORAL: Aligning AI with Human Norms through Multi-Objective Reinforced Active Learning. In Proceedings of the Twenty-First International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 1038–1046, May 2022.
    Please also see the extended version on arXiv.
    Details     Download: pdf [3.1MB]  
15. Miguel Suau, Jinke He, Matthijs T. J. Spaan, and Frans A. Oliehoek. Influence-Augmented Local Simulators: A Scalable Solution for Fast Deep RL in Large Networked Systems. In Proceedings of the 39th International Conference on Machine Learning (ICML), pp. 20604–20624, 2022.
    Details     Download: pdf [1.8MB]  
16. Miguel Suau, Jinke He, Matthijs T.J. Spaan, and Frans A. Oliehoek. Speeding up Deep Reinforcement Learning through Influence-Augmented Local Simulators. In Proceedings of the Twenty-First International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 1735–1737, May 2022.
    Details     Download: pdf [564.4kB]  
17. Jinke He, Miguel Suau, Hendrik Baier, Michael Kaisers, and Frans A. Oliehoek. Online Planning in POMDPs with Self-Improving Simulators. In Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI), pp. 4628–4634, July 2022.
    Details     Download: pdf [2.0MB]  
18. Elise van der Pol, Herke van Hoof, Frans A. Oliehoek, and Max Welling. Multi-Agent MDP Homomorphic Networks. In International Conference on Learning Representations, April 2022.
    Details     Download: pdf [1.9MB]  
19. Jacopo Castellini, Sam Devlin, Frans A. Oliehoek, and Rahul Savani. Difference Rewards Policy Gradients. In Proceedings of the Twentieth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 1475–1477, May 2021.
    Extended Abstract, Please also see the extended version on arXiv.
    Details     Download: pdf [1.5MB]  
20. Elena Congeduti, Alexander Mey, and Frans A. Oliehoek. Loss Bounds for Approximate Influence-Based Abstraction. In Proceedings of the Twentieth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 377–385, May 2021.
    Details     Download: pdf [1.5MB]  
21. Alexander Mey and Frans A. Oliehoek. Environment Shift Games: Are Multiple Agents the Solution, and not the Problem, to Non-Stationarity?. In Proceedings of the Twentieth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 23–27, May 2021. Blue Sky Track. Special Mention.
    Details     Download: pdf [747.7kB]  
22. Canmanie T. Ponnambalam, Frans A. Oliehoek, and Matthijs T. J. Spaan. Abstraction-Guided Policy Recovery from Expert Demonstrations. In Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling, August 2021.
    Details     Download: pdf [989.6kB]  
23. Shi Yuan Tang, Athirai A. Irissappane, Frans A. Oliehoek, and Jie Zhang. Learning Complex Policy Distribution with CEM Guided Adversarial Hypernetwork. In Proceedings of the Twentieth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 1308–1316, May 2021. Invited for JAAMAS fast track
    Details     Download: pdf [2.0MB]  
24. Flavia Alves, Martin Gairing, Frans A. Oliehoek, and Thanh-Toan Do. Sensor Data for Human Activity Recognition: Feature Representation and Benchmarking. In International Joint Conference on Neural Networks (IJCNN), pp. 1–8, 2020.
    Also see arXiv version.
    Details     Download: pdf [521.6kB]  ps.gz ps HTML 
25. Jinke He, Miguel Suau, and Frans A. Oliehoek. Influence-Augmented Online Planning for Complex Environments. In Advances in Neural Information Processing Systems 33, pp. 4392–4402, December 2020.
    Details     Download: pdf [3.0MB]  
26. Mikko Lauri and Frans A. Oliehoek. Multi-agent active perception with prediction rewards. In Advances in Neural Information Processing Systems 33, pp. 13651–13661, December 2020.
    Details     Download: pdf [352.5kB]  
27. Yash Satsangi, Sungsu Lim Lim, Shimon Whiteson, Frans A. Oliehoek, and Martha White. Maximizing Information Gain in Partially Observable Environments via Prediction Rewards. In Proceedings of the Nineteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 1215–1223, May 2020.
    Details     Download: pdf [2.0MB]  
28. Elise Van der Pol, Daniel E. Worrall, Herke Van Hoof, Frans A. Oliehoek, and Max Welling. MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning. In Advances in Neural Information Processing Systems 33, pp. 4199–4210, December 2020.
    Details     Download: pdf [628.1kB]  
29. Elise Van der Pol, Thomas Kipf, Frans A. Oliehoek, and Max Welling. Plannable Approximations to MDP Homomorphisms: Equivariance under Actions. In Proceedings of the Nineteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 1431–1439, May 2020.
    Details     Download: pdf [3.1MB]  
30. Aleksander Czechowski and Frans A. Oliehoek. Decentralized MCTS via Learned Teammate Models. In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI), pp. 81–88, July 2020.
    Details     Download: pdf [415.5kB]  ps.gz ps HTML 
31. Feryal Behbahani, Kyriacos Shiarlis, Xi Chen, Vitaly Kurin, Sudhanshu Kasewa, Ciprian Stirbu, João Gomes, Supratik Paul, Frans A. Oliehoek, João Messias, and Shimon Whiteson. Learning from Demonstration in the Wild. In Proceedings of the 2019 IEEE International Conference on Robotics and Automation, May 2019.
    Details     Download: pdf [4.6MB]  
32. Jacopo Castellini, Frans A. Oliehoek, Rahul Savani, and Shimon Whiteson. The Representational Capacity of Action-Value Networks for Multi-Agent Reinforcement Learning. In Proceedings of the Eighteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 1862–1864, May 2019.
    Extended Abstract, Please also see the extended version on arXiv.
    Details     Download: pdf [593.2kB]  
33. Sammie Katt, Frans A. Oliehoek, and Christopher Amato. Bayesian Reinforcement Learning in Factored POMDPs. In Proceedings of the Eighteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 7–15, May 2019.
    Details     Download: pdf [1004.4kB]  
34. Frans A. Oliehoek. Interactive Learning and Decision Making: Foundations, Insights & Challenges. In Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI), pp. 5703–5708, July 2018.
    Details     Download: pdf [347.0kB]  ps.gz ps HTML 
35. Zhiguang Cao, Hongliang Guo, Jie Zhang, Frans Oliehoek, and Ulrich Fastenrath. Maximizing the Probability of Arriving on Time: A Practical Q-Learning Method. In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI), pp. 4481–4487, February 2017.
    Details     Download: pdf [325.8kB]  
36. Daniel Claes, Frans A. Oliehoek, Hendrik Baier, and Karl Tuyls. Decentralised Online Planning for Multi-Robot Warehouse Commisioning. In Proceedings of the Sixteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 492–500, May 2017. Best paper nominee.
    Details     Download: pdf [798.5kB]  
37. Sammie Katt, Frans A. Oliehoek, and Christopher Amato. Learning in POMDPs with Monte Carlo Tree Search. In Proceedings of the 34th International Conference on Machine Learning (ICML), pp. 1819–1827, August 2017.
    Long version including full proofs available at arXiv: http://arxiv.org/abs/1806.05631
    Details     Download: pdf [478.4kB]  
38. Frans A. Oliehoek, Rahul Savani, Elliot Adderton, Xia Cui, David Jackson, Phil Jimmieson, John Christopher Jones, Keith Kennedy, Ben Mason, Adam Plumbley, and Luke Dawson. LiftUpp: Support to Develop Learner Performance. In Proceedings of the 18th International Conference on Artificial Intelligence in Education (AIED 2017), pp. 553–556, July 2017.
    Long version available at arXiv: http://arxiv.org/abs/1704.06549v1
    Details     Download: pdf [871.9kB]  
39. Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek, and Henri Bouma. Real-Time Resource Allocation for Tracking Systems. In Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence (UAI), August 2017.
    Details     Download: pdf [4.0MB]  
40. Athirai Irissappane, Frans A. Oliehoek, and Jie Zhang. A Scalable Framework to Choose Sellers in E-Marketplaces Using POMDPs. In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI), pp. 158–164, February 2016.
    Details     Download: pdf [341.2kB]  
41. Timon V. Kanters, Frans A. Oliehoek, Michael Kaisers, Stan R. van den Bosch, Joep Grispen, and Jeroen Hermans. Energy- and Cost-Efficient Pumping Station Control. In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI), pp. 3842–3848, February 2016.
    Details     Download: pdf [908.0kB]  
42. Philipp Robbel, Frans A. Oliehoek, and Mykel J. Kochenderfer. Exploiting Anonymity in Approximate Linear Programming: Scaling to Large Multiagent MDPs. In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI), pp. 2537–2543, February 2016.
    Details     Download: pdf [290.3kB]  
43. Yash Satsangi, Shimon Whiteson, and Frans A. Oliehoek. PAC Greedy Maximization with Efficient Bounds on Information Gain for Sensor Selection. In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI), pp. 3220–3227, July 2016.
    Details     Download: pdf [257.2kB]  
44. Yash Satsangi, Shimon Whiteson, and Frans A. Oliehoek. Probably Approximately Correct Greedy Maximization. In Proceedings of the Fifteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 1387–1388, May 2016.
    Extended Abstract, Please also see the extended version on arXiv, as well as the IJCAI version.
    Details     Download: pdf [220.3kB]  
45. Joris Scharpff, Diederik M. Roijers, Frans A. Oliehoek, Matthijs T. J. Spaan, and Mathijs de Weerdt. Solving Transition-Independent Multi-agent MDPs with Sparse Interactions. In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI), pp. 3174–3180, February 2016.
    Also see the extended version on arXiv.
    Details     Download: pdf [593.5kB]  
46. Auke J. Wiggers, Frans A. Oliehoek, and Diederik M. Roijers. Structure in the Value Function of Two-Player Zero-Sum Games of Incomplete Information. In ECAI 2016 - 22nd European Conference on Artificial Intelligence (ECAI), pp. 1628–1629, August 2016.
    [Please also see the extended version on arXiv.
    Details     Download: pdf [171.8kB]  
47. Christopher Amato and Frans A. Oliehoek. Scalable Planning and Learning for Multiagent POMDPs. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), pp. 1995–2002, January 2015.
    [Please see the extended version for pseudo code and proofs.]
    Details     Download: pdf [878.6kB]  
48. Daniel Claes, Philipp Robbel, Frans A. Oliehoek, Daniel Hennes, Karl Tuyls, and Wiebe Van der Hoek. Effective Approximations for Multi-Robot Coordination in Spatially Distributed Tasks. In Proceedings of the Fourteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 881–890, May 2015.
    Details     Download: pdf [383.0kB]  
49. Athirai Irissappane, Jie Zhang, Frans A. Oliehoek, and Partha S. Dutta. Secure Routing in Wireless Sensor Networks via POMDPs. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI), pp. 2617–2623, July 2015.
    Details     Download: pdf [525.7kB]  
50. Frans A. Oliehoek, Matthijs T. J. Spaan, and Stefan Witwicki. Factored Upper Bounds for Multiagent Planning Problems under Uncertainty with Non-Factored Value Functions. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI), pp. 1645–1651, July 2015.
    [Please see the extended version for proofs.]
    Details     Download: pdf [391.5kB]  
51. Frans A. Oliehoek, Matthijs T. J. Spaan, and Stefan Witwicki. Influence-Optimistic Local Values for Multiagent Planning. In Proceedings of the Fourteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 1703–1704, May 2015.
    Extended Abstract. Please see the extended version for details and proofs.
    Details     Download: pdf [142.3kB]  
52. Diederik M. Roijers, Shimon Whiteson, and Frans A. Oliehoek. Point-Based Planning for Multi-Objective POMDPs. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI), pp. 1666–1672, July 2015.
    Details     Download: pdf [759.5kB]  
53. Yash Satsangi, Shimon Whiteson, and Frans A. Oliehoek. Exploiting Submodular Value Functions for Faster Dynamic Sensor Selection. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), pp. 3356–3363, January 2015.
    Details     Download: pdf [676.0kB]  
54. Athirai Irissappane, Frans A. Oliehoek, and Jie Zhang. A POMDP Based Approach to Optimally Select Sellers in Electronic Marketplaces. In Proceedings of the Thirteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 1329–1336, May 2014.
    Details     Download: pdf [532.9kB]  
55. Diederik M. Roijers, Shimon Whiteson, and Frans A. Oliehoek. Linear Support for Multi-Objective Coordination Graphs. In Proceedings of the Thirteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 1297–1304, May 2014.
    Details     Download: pdf [506.9kB]  
56. Diederik M. Roijers, Joris Scharpff, Matthijs Spaan, Frans A. Oliehoek, Mathijs De Weerdt, and Shimon Whiteson. Bounded Approximations for Linear Multi-Objective Planning under Uncertainty. In Proceedings of the Twenty-Fourth International Conference on Automated Planning and Scheduling, pp. 262–270, June 2014.
    Details     Download: pdf [385.0kB]  
57. Frans A. Oliehoek. Sufficient Plan-Time Statistics for Decentralized POMDPs. In Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI), pp. 302–308, 2013.
    Details     Download: pdf [266.0kB]  
58. Frans A. Oliehoek, Shimon Whiteson, and Matthijs T. J. Spaan. Approximate Solutions for Factored Dec-POMDPs with Many Agents. In Proceedings of the Twelfth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 563–570, 2013.
    Details     Download: pdf [238.2kB]  
59. Diederik M. Roijers, Shimon Whiteson, and Frans A. Oliehoek. Computing Convex Coverage Sets for Multi-Objective Coordination Graphs. In Proceedings of the Third International Conference on Algorithmic Decision Theory (ADT), pp. 309–323, November 2013.
    Details     Download: pdf [1.2MB]  ps.gz ps HTML 
60. Diederik M. Roijers, Shimon Whiteson, and Frans A. Oliehoek. Multi-Objective Variable Elimination for Collaborative Graphical Games. In Proceedings of the Twelfth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 1209–1210, 2013.
    Extended Abstract
    Details     Download: pdf [315.5kB]  
61. Frans A. Oliehoek, Shimon Whiteson, and Matthijs T. J. Spaan. Exploiting Structure in Cooperative Bayesian Games. In Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI), pp. 654–664, August 2012.
    Details     Download: pdf [1.2MB]  
62. Frans A. Oliehoek and Matthijs T. J. Spaan. Tree-Based Solution Methods for Multiagent POMDPs with Delayed Communication. In Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI), pp. 1415–1421, July 2012.
    Details     Download: pdf [145.0kB]  
63. Frans A. Oliehoek, Stefan Witwicki, and Leslie P. Kaelbling. Influence-Based Abstraction for Multiagent Systems. In Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI), pp. 1422–1428, July 2012.
    Details     Download: pdf [159.8kB]  
64. Frans A. Oliehoek and Matthijs T. J. Spaan. Tree-based Pruning for Multiagent POMDPs with Delayed Communication. In Proceedings of the Eleventh International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 1229–1230, June 2012.
    Extended abstract.
    Details     Download: pdf [95.6kB]  
65. Stefan Witwicki, Frans A. Oliehoek, and Leslie P. Kaelbling. Heuristic Search of Multiagent Influence Space. In Proceedings of the Eleventh International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 973–981, June 2012.
    Details     Download: pdf [583.5kB]  
66. Matthijs T. J. Spaan, Frans A. Oliehoek, and Christopher Amato. Scaling Up Optimal Heuristic Search in Dec-POMDPs via Incremental Expansion. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence (IJCAI), pp. 2027–2032, 2011.
    Details     Download: pdf [130.3kB]  ps.gz ps HTML 
67. Frans A. Oliehoek, Matthijs T. J. Spaan, Jilles Dibangoye, and Christopher Amato. Heuristic Search for Identical Payoff Bayesian Games. In Proceedings of the Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 1115–1122, May 2010.
    Details     Download: pdf [179.3kB]  
68. Frans A. Oliehoek, Shimon Whiteson, and Matthijs T. J. Spaan. Lossless Clustering of Histories in Decentralized POMDPs. In Proceedings of the Eighth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 577–584, May 2009.
    Details     Download: pdf [209.6kB]  
69. Frans A. Oliehoek, Matthijs T. J. Spaan, Shimon Whiteson, and Nikos Vlassis. Exploiting Locality of Interaction in Factored Dec-POMDPs. In Proceedings of the Seventh Joint International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 517–524, May 2008.
    Details     Download: pdf [2.1MB]  ps.gz [375.3kB]  
70. Matthijs T. J. Spaan, Frans A. Oliehoek, and Nikos Vlassis. Multiagent Planning under Uncertainty with Stochastic Communication Delays. In Proceedings of the Eighteenth International Conference on Automated Planning and Scheduling, pp. 338–345, September 2008.
    Details     Download: pdf [141.2kB]  
71. Frans A. Oliehoek, Julian F. P. Kooij, and Nikos Vlassis. A Cross-Entropy Approach to Solving Dec-POMDPs. In Proceedings of the 1st International Symposium on Intelligent and Distributed Computing (IDC), pp. 145–154, October 2007.
    Details     Download: pdf [146.8kB]  ps.gz [376.0kB]  
72. Frans A. Oliehoek and Nikos Vlassis. Q-value Functions for Decentralized POMDPs. In Proceedings of the Sixth Joint International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 833–840, May 2007.
    Details     Download: pdf [171.2kB]  ps.gz [163.9kB]  
73. Frans A. Oliehoek, Edwin D. de Jong, and Nikos Vlassis. The Parallel Nash Memory for Asymmetric Games. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pp. 337–344, July 2006. Best paper nominee in coevolution track
    Details     Download: pdf [174.6kB]  ps.gz [172.6kB]  ps HTML 

Refereed Conference (Local)

1. Rolf A. N. Starre, Marco Loog, and Frans A. Oliehoek. Model-Based Reinforcement Learning with State Abstraction: A Survey. In Proceedings of the 34th Benelux Conference on Artificial Intelligence (BNAIC) and the 30th Belgian Dutch Conference on Machine Learning (Benelearn), pp. 73–89, Springer International Publishing, 2023.
   Details     Download: pdf [352.8kB]  ps.gz ps HTML 
2. Victoria Catalan Pastor, Elena Congeduti, Aleksander Czechowski, and Frans A. Oliehoek. Overcoming Traffic Sensors Malfunctions with Deep Learning. In Proceedings of the 34th Benelux Conference on Artificial Intelligence (BNAIC) and the 30th Belgian Dutch Conference on Machine Learning (Benelearn), November 2022.
   Details     Download: pdf [1.2MB]  
3. Elena Congeduti and Frans A. Oliehoek. A Cross-Field Review of State Abstraction for Markov Decision Processes. In Proceedings of the 34th Benelux Conference on Artificial Intelligence (BNAIC) and the 30th Belgian Dutch Conference on Machine Learning (Benelearn), November 2022.
   Details     Download: pdf [437.1kB]  
4. Rolf A. N. Starre, Marco Loog, and Frans A. Oliehoek. Model-Based Reinforcement Learning with State Abstraction: A Survey. In Proceedings of the 34th Benelux Conference on Artificial Intelligence (BNAIC) and the 30th Belgian Dutch Conference on Machine Learning (Benelearn), November 2022.
   Details     Download: pdf [352.9kB]  
5. Nele Albers, Miguel Suau, and Frans A. Oliehoek. Using Bisimulation Metrics to Analyze and Evaluate Latent State Representations. In Proceedings of the 33rd Benelux Conference on Artificial Intelligence (BNAIC) and the 29th Belgian Dutch Conference on Machine Learning (Benelearn), pp. 320–334, November 2021.
   Details     Download: pdf [5.4MB]  
6. Nele Albers, Miguel Suau, and Frans A. Oliehoek. Learning What to Attend to: Using Bisimulation Metrics to Explore and Improve Upon What a Deep Reinforcement Learning Agent Learns. In Proceedings of the 32nd Benelux Conference on Artificial Intelligence (BNAIC) and the 29th Belgian Dutch Conference on Machine Learning (Benelearn), November 2020.
   Details     Download: pdf [243.5kB]  
7. Alexander Mandersloot, Frans A. Oliehoek, and Aleksander Czechowski. Exploring the Effects of Conditioning Independent Q-Learners on the Sufficient Statistic for Dec-POMDPs. In Proceedings of the 32nd Benelux Conference on Artificial Intelligence (BNAIC) and the 29th Belgian Dutch Conference on Machine Learning (Benelearn), November 2020.
   Details     Download: pdf [1.0MB]  
8. Yaniv Oren, Rolf A. N., Starre, and Frans A. Oliehoek. Comparing Exploration Approaches in Deep Reinforcement Learning for Traffic Light Control. In Proceedings of the 32nd Benelux Conference on Artificial Intelligence (BNAIC) and the 29th Belgian Dutch Conference on Machine Learning (Benelearn), November 2020.
   Details     Download: pdf [976.0kB]  
9. Frans A. Oliehoek, Rahul Savani, Jose Gallego, Elise van der Pol, and Roderich Groß. Beyond Local Nash Equilibria for Adversarial Networks. In Artificial Intelligence, pp. 73–89, Springer International Publishing, September 2019.
   Also see arXiv version.
   Details     Download: pdf [1.3MB]  ps.gz ps HTML 
10. Frans A. Oliehoek, Rahul Savani, Jose Gallego-Posada, Elise van der Pol, and Roderich Gross. Beyond Local Nash Equilibria for Adversarial Networks. In Proceedings of the 27th Annual Machine Learning Conference of Belgium and the Netherlands (Benelearn), November 2018.
    Long version at arxiv: arXiv.
    Details     Download: pdf [1.3MB]  
11. Joris Scharpff, Diederik M. Roijers, Frans A. Oliehoek, Matthijs T. J. Spaan, and Mathijs de Weerdt. Conditional Return Policy Search for TI-MMDPs with Sparse Interactions. In Proceedings of the 28th Belgian-Dutch Conference on Artificial Intelligence (BNAIC), November 2016.
    Extended Abstract
    Details     Download: pdf [207.7kB]  
12. Elise Van der Pol and Frans A. Oliehoek. Video Demo: Deep Reinforcement Learning for Coordination in Traffic Light Control. In Proceedings of the 28th Belgian-Dutch Conference on Artificial Intelligence (BNAIC), November 2016.
    See video at www.fransoliehoek.net/trafficvideo.
    Details     Download: pdf [91.8kB]  
13. Luisa M. Zintgraf, Timon V. Kanters, Diederik M. Roijers, Frans A. Oliehoek, and Philipp Beau. Quality Assessment of MORL Algorithms: A Utility-Based Approach. In Proceedings of the 24th Annual Machine Learning Conference of Belgium and the Netherlands (Benelearn), 2015.
    Details     Download: pdf [292.2kB]  
14. Diederik M. Roijers, Joris Scharpff, Matthijs Spaan, Frans A. Oliehoek, Mathijs De Weerdt, and Shimon Whiteson. Bounded Approximations for Linear Multi-Objective Planning under Uncertainty (Extended Abstract). In Proceedings of the 26th Belgian-Dutch Conference on Artificial Intelligence (BNAIC), pp. 168–169, November 2014.
    Extended Abstract.
    Details     Download: pdf [135.5kB]  
15. Daniel Claes, Philipp Robbel, Frans A. Oliehoek, Daniel Hennes, and Karl Tuyls. Effective Approximations for Spatial Task Allocation Problems. In Proceedings of the 25th Belgian-Dutch Conference on Artificial Intelligence (BNAIC), pp. 33–40, 2013. Best paper runner up.
    Details     Download: pdf [363.4kB]  
16. Julia Efremova, Bijan Ranjbar-Sahraei, Frans A. Oliehoek, Toon Calders, and Karl Tuyls. An Interactive, Web-based Tool for Genealogical Entity Resolution. In Proceedings of the 25th Belgian-Dutch Conference on Artificial Intelligence (BNAIC), pp. 376–377, 2013. Demo-track.
    Details     Download: pdf [132.2kB]  
17. Frans A. Oliehoek, Shimon Whiteson, and Matthijs T. J. Spaan. Approximate Solutions for Factored Dec-POMDPs with Many Agents --- Extended Abstract. In Proceedings of the 25th Belgian-Dutch Conference on Artificial Intelligence (BNAIC), pp. 340–341, 2013.
    Details     Download: pdf [451.2kB]  
18. Frans A. Oliehoek, Stefan Witwicki, and Leslie P. Kaelbling. Influence-Based Abstraction for Multiagent Systems. In Proceedings of the 24th Belgian-Dutch Conference on Artificial Intelligence (BNAIC), pp. 311–312, 2012.
    Extended Abstract.
    Details     Download: HTML 
19. Matthijs T. J. Spaan and Frans A. Oliehoek. Tree-Based Solution Methods for Multiagent POMDPs with Delayed Communication. In Proceedings of the 24th Belgian-Dutch Conference on Artificial Intelligence (BNAIC), pp. 319–320, 2012.
    Extended Abstract.
    Details     Download: HTML 
20. Matthijs T. J. Spaan, Frans A. Oliehoek, and Christopher Amato. Scaling Up Optimal Heuristic Search in Dec-POMDPs via Incremental Expansion. In Proceedings of the 23rd Belgian-Dutch Conference on Artificial Intelligence (BNAIC), pp. 433–434, 2011.
    Extended Abstract.
    Details     Download: pdf [32.0kB]  
21. Frans A. Oliehoek, Nikos Vlassis, and Edwin de Jong. Coevolutionary Nash in Poker Games. In Proceedings of the 17th Belgian-Dutch Conference on Artificial Intelligence (BNAIC), pp. 188–193, October 2005.
    Details     Download: pdf [139.2kB]  ps.gz [128.2kB]  
22. Frans A. Oliehoek, Matthijs T. J. Spaan, and Nikos Vlassis. Best-response Play in Partially Observable Card Games. In Proceedings of the 14th Annual Machine Learning Conference of Belgium and the Netherlands (Benelearn), pp. 45–50, February 2005.
    Details     Download: pdf [115.6kB]  

Refereed Workshop

1. Raphaël Avalos, Eugenio Bargiacchi, Ann Nowe, Diederik Roijers, and Frans A Oliehoek. Online Planning in POMDPs with State-Requests. In Seventeenth European Workshop on Reinforcement Learning (EWRL), October 2024.
   Details     Download: pdf [488.1kB]  
2. Oussama Azizi, Philip Boeken, Onno Zoeter, Frans A Oliehoek, and Matthijs T. J. Spaan. Leveraging diverse offline data in POMDPs with unobserved confounders. In Seventeenth European Workshop on Reinforcement Learning (EWRL), October 2024.
   Details     Download: pdf [615.6kB]  
3. Jan Wehner, Frans Oliehoek, and Luciano Cavalcante Siebert. Explaining Learned Reward Functions with Counterfactual Trajectories. In ECAI 2024 Workshop on Implementing AI Ethics Through a Behavioural Lens, October 2024.
   Details     Download: pdf [354.8kB]  
4. Robert Loftin, Mustafa Mert Çelikok, Herke van Hoof, Samuel Kaski, and Frans A. Oliehoek. Uncoupled Learning of Differential Stackelberg Equilibria with Commitments. In Proceedings of the AAMAS Workshop on Adaptive Learning Agents (ALA), 2023.
   Details     Download: pdf [482.2kB]  
5. Robert Loftin, Mustafa Mert Çelikok, and Frans A. Oliehoek. Towards a Unifying Model of Rationality in Multiagent Systems. In AAMAS Workshop on Optimization and Learning in Multiagent Systems, 2023.
   Details     Download: pdf [143.8kB]  
6. Miguel Suau, Matthijs T. J. Spaan, and Frans A. Oliehoek. Bad Habits: Policy Confounding and Out-of-Trajectory Generalization in RL. In European Workshop on Reinforcement Learning (EWRL), 2023.
   Details     Download: pdf [942.5kB]  
7. Daniele Foffano, Jinke He, and Frans A. Oliehoek. Robust Ensemble Adversarial Model-Based Reinforcement Learning. In Proceedings of the AAMAS Workshop on Adaptive Learning Agents (ALA), May 2022.
   Details     Download: pdf [624.8kB]  
8. Canmanie T. Ponnambalam, Danial Kamran, Thiago Dias Simão, Frans A. Oliehoek, and Matthijs T. J. Spaan. Back to the Future: Solving Hidden Parameter MDPs with Hindsight. In Proceedings of the AAMAS Workshop on Adaptive Learning Agents (ALA), May 2022.
   Details     Download: pdf [3.3MB]  
9. Jacopo Castellini, Sam Devlin, Frans A. Oliehoek, and Rahul Savani. Difference Rewards Policy Gradients. In Proceedings of the AAMAS Workshop on Adaptive Learning Agents (ALA), May 2021. Best paper award.
   Details     Download: pdf [1.5MB]  
10. Jordi Smit, Canmanie Ponnambalam, Matthijs T.J. Spaan, and Frans A. Oliehoek. PEBL: Pessimistic Ensembles for Offline Deep Reinforcement Learning. In IJCAI Workshop on Robust and Reliable Autonomy in the Wild (R2AW), August 2021.
    Details     Download: pdf [334.3kB]  
11. Burak Yildiz, Hayley Hung, Jesse H. Krijthe, Cynthia C. S. Liem, Marco Loog, Gosia Migut, Frans Oliehoek, Annibale Panichella, Przemyslaw Pawelczak, Stjepan Picek, Mathijs de Weerdt, and Jan van Gemert. ReproducedPapers.org: Openly teaching and structuring machine learning reproducibility. In RRPR 2020: Third Workshop on Reproducible Research in Pattern Recognition, 2021.
    Please also see the version on arXiv.
    Details     Download: pdf [334.4kB]  
12. Canmanie T. Ponnambalam, Frans A. Oliehoek, and Matthijs T. J. Spaan. Abstraction-Guided Policy Recovery from Expert Demonstrations. In NeurIPS'20 Workshop on Offline Reinforcement Learning, December 2020.
    Details     Download: pdf [233.6kB]  
13. Miguel Suau de Castro, Elena Congeduti, Jinkte He, Rolf A.N. Starre, Aleksander Czechowski, and Frans A. Oliehoek. Influence-aware Memory for Deep Reinforcement Learning. In NeurIPS'20 Workshop on Deep Reinforcement Learning, December 2020.
    Details     Download: pdf [548.4kB]  
14. Wook Lee and Frans A. Oliehoek. Analog Circuit Design with Dyna-Style Reinforcement Learning. In NeurIPS'20 Workshop on Machine Learning for Engineering Modeling, Simulation, and Design, pp. arXiv:2011.07665, December 2020.
    Details     Download: pdf [527.5kB]  
15. Miguel Suau de Castro, Elena Congeduti, Rolf A.N. Starre, Aleksander Czechowski, and Frans A. Oliehoek. Influence-Based Abstraction in Deep Reinforcement Learning. In Proceedings of the AAMAS Workshop on Adaptive Learning Agents (ALA), May 2019.
    Details     Download: pdf [805.9kB]  
16. Sammie Katt, Frans A. Oliehoek, and Christopher Amato. MCTS on model-based Bayesian Reinforcement Learning for efficient learning in Partially Observable environments. In NeurIPS Workshop on Reinforcement Learning under Partial Observability, December 2018.
    Details     Download: pdf [240.0kB]  
17. Sammie Katt, Frans A. Oliehoek, and Christopher Amato. Efficient Exploitation of Factored Domains in Bayesian Reinforcement Learning for POMDPs. In Proceedings of the AAMAS Workshop on Adaptive Learning Agents (ALA), July 2018.
    Details     Download: pdf [826.1kB]  
18. Richard Klima, Karl Tuyls, and Frans A. Oliehoek. Model-Based Reinforcement Learning under Periodical Observability. In AAAI Spring Symposium on Learning, Inference and Control of Multi-Agent Systems (MALIC), March 2018.
    Details     Download: pdf [1.6MB]  
19. Richard Klima, Karl Tuyls, and Frans A. Oliehoek. Markov Security Games: Learning in Spatial Security Problems. In NIPS'16 Workshop on Learning, Inference and Control of Multi-Agent Systems, December 2016.
    Details     Download: pdf [238.3kB]  
20. Elise Van der Pol and Frans A. Oliehoek. Coordinated Deep Reinforcement Learners for Traffic Light Control. In NIPS'16 Workshop on Learning, Inference and Control of Multi-Agent Systems, December 2016.
    Details     Download: pdf [341.5kB]  
21. Daniel Claes, Philipp Robbel, Frans A. Oliehoek, Daniel Hennes, Karl Tuyls, and Wiebe Van der Hoek. Effective Approximations for Multi-Robot Coordination in Spatially Distributed Tasks. In Proceedings of the Tenth AAMAS Workshop on Multi-Agent Sequential Decision Making in Uncertain Domains (MSDM), May 2015.
    Details     Download: pdf [382.0kB]  
22. Frans A. Oliehoek, Matthijs T. J. Spaan, Philipp Robbel, and João V. Messias. The MADP Toolbox: An Open-Source Library for Planning and Learning in (Multi-)Agent Systems. In Sequential Decision Making for Intelligent Agents---Papers from the AAAI 2015 Fall Symposium, pp. 59–62, November 2015.
    Details     Download: pdf [124.7kB]  
23. Frans A. Oliehoek, Matthijs T. J. Spaan, and Stefan Witwicki. Influence-Optimistic Local Values for Multiagent Planning. In Proceedings of the Tenth AAMAS Workshop on Multi-Agent Sequential Decision Making in Uncertain Domains (MSDM), May 2015.
    [Please see the extended version for proofs.]
    Details     Download: pdf [2.7MB]  
24. Philipp Robbel, Frans A. Oliehoek, and Mykel J. Kochenderfer. Exploiting Anonymity in Approximate Linear Programming: Scaling to Large Multiagent MDPs. In Proceedings of the AAAI Fall Symposium on Sequential Decision Making in Intelligent Agents, November 2015.
    Details     Download: pdf [336.3kB]  
25. Diederik M. Roijers, Shimon Whiteson, Alex Ihler, and Frans A. Oliehoek. Variational Multi-Objective Coordination. In NIPS Workshop on Learning, Inference and Control of Multi-Agent Systems, December 2015.
    Details     Download: pdf [1.1MB]  
26. Joris Scharpff, Diederik M. Roijers, Frans A. Oliehoek, Matthijs T. J. Spaan, and Mathijs de Weerdt. Solving Multi-agent MDPs Optimally with Conditional Return Graphs. In Proceedings of the Tenth AAMAS Workshop on Multi-Agent Sequential Decision Making in Uncertain Domains (MSDM), May 2015.
    Details     Download: pdf [580.8kB]  
27. Auke J. Wiggers, Frans A. Oliehoek, and Diederik M. Roijers. Structure in the Value Function of Zero-Sum Games of Incomplete Information. In Proceedings of the Tenth AAMAS Workshop on Multi-Agent Sequential Decision Making in Uncertain Domains (MSDM), May 2015.
    Details     Download: pdf [296.2kB]  
28. Julia Efremova, Bijan Ranjbar-Sahraei, Frans A. Oliehoek, Toon Calders, and Karl Tuyls. A Baseline Method for Genealogical Entity Resolution. In Proceedings of the Workshop on Population Reconstruction, January 2014.
    Details     Download: pdf [642.7kB]  
29. Frans A. Oliehoek and Christopher Amato. Best Response Bayesian Reinforcement Learning for Multiagent Systems with State Uncertainty. In Proceedings of the Ninth AAMAS Workshop on Multi-Agent Sequential Decision Making in Uncertain Domains (MSDM), 2014.
    Details     Download: pdf [231.1kB]  
30. Christopher Amato, Frans A. Oliehoek, and Eric Shyu. Scalable Bayesian Reinforcement Learning for Multiagent POMDPs. In Proceedings of the First Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM), 2013.
    Details     Download: pdf [506.8kB]  
31. Christopher Amato and Frans A. Oliehoek. Bayesian Reinforcement Learning for Multiagent Systems with State Uncertainty. In Proceedings of the Eighth AAMAS Workshop on Multi-Agent Sequential Decision Making in Uncertain Domains (MSDM), pp. 76–83, 2013.
    Details     Download: pdf [177.5kB]  
32. Frans A. Oliehoek, Ashwini A. Gokhale, and Jie Zhang. Reasoning about Advisors for Seller Selection in E-Marketplaces via POMDPs. In 15th International Workshop on Trust in Agent Societies (TRUST), pp. 67–78, June 2012.
    Details     Download: pdf [227.3kB]  
33. Frans A. Oliehoek and Matthijs T. J. Spaan. Tree-Based Solution Methods for Multiagent POMDPs with Delayed Communication. In Proceedings of the Seventh AAMAS Workshop on Multi-Agent Sequential Decision Making in Uncertain Domains (MSDM), pp. 48–55, June 2012.
    (longer version of AAAI)
    Details     Download: pdf [200.6kB]  
34. Frans A. Oliehoek, Stefan Witwicki, and Leslie P. Kaelbling. Heuristic Search of Multiagent Influence Space. In Proceedings of the 9th European Workshop on Multi-agent Systems (EUMAS 2011), 2011.
    Details     Download: pdf [4.4MB]  
35. Matthijs T. J. Spaan, Frans A. Oliehoek, and Christopher Amato. Scaling Up Optimal Heuristic Search in Dec-POMDPs via Incremental Expansion. In Proceedings of the Sixth AAMAS Workshop on Multi-Agent Sequential Decision Making in Uncertain Domains (MSDM), pp. 63–70, 2011.
    Details     Download: pdf [229.0kB]  
36. Matthijs T. J. Spaan and Frans A. Oliehoek. The MultiAgent Decision Process Toolbox: Software for Decision-theoretic Planning in Multiagent Systems. In Proceedings of the Third AAMAS Workshop on Multi-Agent Sequential Decision Making in Uncertain Domains (MSDM), pp. 107–121, 2008.
    Details     Download: pdf [178.7kB]  
37. Frans A. Oliehoek, Matthijs T. J. Spaan, and Nikos Vlassis. Dec-POMDPs with delayed communication. In Proceedings of the Second AAMAS Workshop on Multi-Agent Sequential Decision Making in Uncertain Domains (MSDM), May 2007.
    Details     Download: pdf [146.0kB]  ps.gz [107.9kB]  
38. Frans A. Oliehoek and Nikos Vlassis. Q-value Heuristics for Approximate Solutions of Dec-POMDPs. In Proceedings of the AAAI Spring Symposium on Game Theoretic and Decision Theoretic Agents, pp. 31–37, March 2007.
    Details     Download: pdf [637.6kB]  ps.gz [99.9kB]  
39. Frans A. Oliehoek and Arnoud Visser. A Hierarchical Model for Decentralized Fighting of Large Scale Urban Fires. In Proceedings of the AAMAS Workshop on Hierarchical Autonomous Agents and Multi-Agent Systems, pp. 14–21, May 2006.
    Details     Download: pdf [140.1kB]  ps.gz [145.2kB]  

Technical Report

1. Frans A. Oliehoek and Christopher Amato. Dec-POMDPs as Non-Observable MDPs. IAS technical report IAS-UVA-14-01, Intelligent Systems Lab, University of Amsterdam, 2014.
   Details     Download: pdf [235.2kB]  
2. Yash Satsangi, Shimon Whiteson, and Frans A. Oliehoek. Exploiting Submodular Value Functions for Faster Dynamic Sensor Selection: Extended Version. IAS technical report IAS-UVA-14-01, Intelligent Systems Lab, University of Amsterdam, 2014.
   Details     Download: pdf [767.4kB]  
3. Frans A. Oliehoek, Nikos Vlassis, and Matthijs T. J. Spaan. Properties of the QBG-value Function. IAS technical report IAS-UVA-07-04, Intelligent Systems Lab, University of Amsterdam, 2007.
   Details     Download: pdf [197.0kB]  ps.gz [203.0kB]  
4. Frans A. Oliehoek and Nikos Vlassis. Dec-POMDPs and extensive form games: equivalence of models and algorithms. IAS technical report IAS-UVA-06-02, Intelligent Systems Lab, University of Amsterdam, 2006.
   Details     Download: pdf [404.3kB]  ps.gz [345.7kB]  

arXiv

1. Mustafa Mert Çelikok, Frans A. Oliehoek, and Jan-Willem van de Meent. Inverse Concave-Utility Reinforcement Learning is Inverse Game Theory. arXiv e-prints, pp. arXiv:2405.19024, May 2024.
   Details     Download: pdf ps.gz ps HTML 
2. Pengzhi Yang, Xinyu Wang, Ruipeng Zhang, Cong Wang, Frans A. Oliehoek, and Jens Kober. Task-unaware Lifelong Robot Learning with Retrieval-based Weighted Local Adaptation. arXiv e-prints, 2024.
   Details     Download: HTML 
3. Davide Mambelli, Stephan Bongers, Onno Zoeter, Matthijs T. J. Spaan, and Frans A. Oliehoek. When Do Off-Policy and On-Policy Policy Gradient Methods Align?. arXiv e-prints, pp. arXiv:2402.12034, February 2024.
   Details     Download: pdf ps.gz ps HTML 
4. Jan Wehner, Frans Oliehoek, and Luciano Cavalcante Siebert. Explaining Learned Reward Functions with Counterfactual Trajectories. arXiv e-prints, pp. arXiv:2402.04856, February 2024.
   Details     Download: pdf ps.gz ps HTML 
5. Jinke He, Thomas M. Moerland, and Frans A. Oliehoek. What model does MuZero learn?. arXiv e-prints, pp. arXiv:2306.00840, June 2023.
   Details     Download: pdf ps.gz ps HTML 
6. Frans A. Oliehoek, Elena Congeduti, Aleksander Czechowski, Jinke He, Alexander Mey, Rolf A.N. Starre, and Miguel Suau. About `Influence'. Blog, 2022.
   https://www.fransoliehoek.net/wp/2022/02/01/a-blog-about-influence/
   Details     Download: pdf [408.4kB]  
7. Miguel Suau, Jinke He, Matthijs T.J. Spaan, and Frans A. Oliehoek. Influence-Augmented Local Simulators: A Scalable Solution for Fast Deep RL in Large Networked Systems. arXiv e-prints, pp. arXiv:2202.01534, February 2022.
   Details     Download: pdf [1.1MB]  
8. Jinke He, Miguel Suau, Hendrik Baier, Michael Kaisers, and Frans A. Oliehoek. Online Planning in POMDPs with Self-Improving Simulators. arXiv e-prints, pp. arXiv:2201.11404, January 2022.
   Details     Download: HTML 
9. Rolf A. N. Starre, Marco Loog, and Frans A. Oliehoek. An Analysis of Abstracted Model-Based Reinforcement Learning. arXiv e-prints, pp. arXiv:2208.14407, August 2022.
   Details     Download: (unavailable)
10. Miguel Suau, Jinke He, Mustafa Mert Çelikok, Matthijs T. J. Spaan, and Frans A. Oliehoek. Distributed Influence-Augmented Local Simulators for Parallel MARL in Large Networked Systems. arXiv e-prints, pp. arXiv:2207.00288, July 2022.
    Details     Download: (unavailable)
11. Elise van der Pol, Herke van Hoof, Frans A. Oliehoek, and Max Welling. Multi-Agent MDP Homomorphic Networks. arXiv e-prints, pp. arXiv:2110.04495, October 2021.
    Details     Download: (unavailable)
12. João P. Abrantes, Arnaldo J. Abrantes, and Frans A. Oliehoek. Mimicking Evolution with Reinforcement Learning. arXiv e-prints, pp. arXiv:2004.00048, March 2020.
    Details     Download: pdf [936.3kB]  
13. Elena Congeduti, Alexander Mey, and Frans A. Oliehoek. Loss Bounds for Approximate Influence-Based Abstraction. arXiv e-prints, pp. arXiv:2011.01788, November 2020.
    Details     Download: pdf [1.2MB]  
14. Aleksander Czechowski and Frans Oliehoek. Decentralized MCTS via Learned Teammate Models. arXiv e-prints, pp. arXiv:2003.08727, March 2020.
    Details     Download: pdf [411.7kB]  
15. Christian Muench, Frans A. Oliehoek, and Dariu M. Gavrila. Diversity in Action: General-Sum Multi-Agent Continuous Inverse Optimal Control. arXiv e-prints, pp. arXiv:2004.12678, April 2020.
    Details     Download: pdf [581.4kB]  
16. Burak Yildiz, Hayley Hung, Jesse H. Krijthe, Cynthia C. S. Liem, Marco Loog, Gosia Migut, Frans Oliehoek, Annibale Panichella, Przemyslaw Pawelczak, Stjepan Picek, Mathijs de Weerdt, and Jan van Gemert. ReproducedPapers.org: Openly teaching and structuring machine learning reproducibility. arXiv e-prints, pp. arXiv:2012.01172, December 2020.
    Details     Download: pdf [378.5kB]  
17. Jacopo Castellini, Frans A. Oliehoek, Rahul Savani, and Shimon Whiteson. The Representational Capacity of Action-Value Networks for Multi-Agent Reinforcement Learning. arXiv e-prints, pp. arXiv:1902.07497, February 2019.
    Extended version of AAMAS paper
    Details     Download: pdf [1.7MB]  
18. Miguel Suau de Castro, Elena Congeduti, Rolf A.N. Starre, Aleksander Czechowski, and Frans A. Oliehoek. Influence-aware Memory for Deep Reinforcement Learning. arXiv e-prints, pp. arXiv:1911.07643, Nov 2019.
    Details     Download: pdf [1.5MB]  
19. Frans A. Oliehoek, Stefan Witwicki, and Leslie P. Kaelbling. A Sufficient Statistic for Influence in Structured Multiagent Environments. arXiv e-prints, pp. arXiv:1907.09278, July 2019. Published in JAIR.
    Details     Download: pdf [558.3kB]  
20. Sammie Katt, Frans A. Oliehoek, and Christopher Amato. Bayesian Reinforcement Learning in Factored POMDPs. arXiv e-prints, pp. arXiv:1811.05612, November 2018.
    Also available from arXiv.
    Details     Download: pdf [856.3kB]  
21. Sammie Katt, Frans A. Oliehoek, and Christopher Amato. Learning in POMDPs with Monte Carlo Tree Search. ArXiv e-prints, June 2018.
    Version of our ICML paper including all proofs, also available from arXiv.
    Details     Download: pdf [596.8kB]  
22. Frans A. Oliehoek, Rahul Savani, Jose Gallego-Posada, Elise van der Pol, and Roderich Gross. Beyond Local Nash Equilibria for Adversarial Networks. ArXiv e-prints, June 2018.
    Also available from arXiv.
    Details     Download: pdf [2.6MB]  
23. Feryal Behbahani, Kyriacos Shiarlis, Xi Chen, Vitaly Kurin, Sudhanshu Kasewa, Ciprian Stirbu, João Gomes, Supratik Paul, Frans A. Oliehoek, João Messias, and Shimon Whiteson. Learning from Demonstration in the Wild. arXiv e-prints, pp. arXiv:1811.03516, November 2018.
    Accepted for publcation at ICRA
    Details     Download: pdf [4.5MB]  
24. Frans  A. Oliehoek, Rahul Savani, Jose Gallego-Posada, Elise Van der Pol, Edwin D. De Jong, and Roderich Groß. GANGs: Generative Adversarial Network Games. ArXiv e-prints, December 2017.
    Details     Download: pdf [2.7MB]  
25. Frans  A. Oliehoek, Rahul Savani, Elliot Adderton, Xia Cui, David Jackson, Phil Jimmieson, John Christopher Jones, Keith Kennedy, Ben Mason, Adam Plumbley, and Luke Dawson. LiftUpp: Support to develop learner performance. ArXiv e-prints, April 2017.
    Details     Download: pdf [1.9MB]  
26. Philipp Robbel, Frans A. Oliehoek, and Mykel J. Kochenderfer. Exploiting Anonymity in Approximate Linear Programming: Scaling to Large Multiagent MDPs (Extended Version). ArXiv e-prints, arXiv:1511.09080, February 2016.
    Details     Download: pdf [392.8kB]  
27. Yash Satsangi, Shimon Whiteson, and Frans A. Oliehoek. Probably Approximately Correct Greedy Maximization. ArXiv e-prints, arXiv:1602.07860, February 2016.
    Details     Download: pdf [319.1kB]  
28. Joris Scharpff, Diederik M. Roijers, Frans A. Oliehoek, Matthijs T. J. Spaan, and Mathijs de Weerdt. Solving Transition-Independent Multi-agent MDPs with Sparse Interactions (Extended version). ArXiv e-prints, arXiv:1511.09047, February 2016.
    Details     Download: HTML 
29. Auke J. Wiggers, Frans A. Oliehoek, and Diederik M. Roijers. Structure in the Value Function of Two-Player Zero-Sum Games of Incomplete Information. ArXiv e-prints, arXiv:1606.06888, June 2016.
    Details     Download: pdf [183.0kB]  
30. Athirai Irissappane, Frans A. Oliehoek, and Jie Zhang. Scaling POMDPs For Selecting Sellers in E-markets---Extended Version. ArXiv e-prints, arXiv:1511.09147, December 2015.
    Details     Download: pdf [588.2kB]  
31. Frans A. Oliehoek, Matthijs T. J. Spaan, and Stefan Witwicki. Influence-Optimistic Local Values for Multiagent Planning --- Extended Version. ArXiv e-prints, arXiv:1502.05443, February 2015.
    Details     Download: pdf [686.9kB]  
32. Christopher Amato and Frans A. Oliehoek. Scalable Planning and Learning for Multiagent POMDPs: Extended Version. ArXiv e-prints, arXiv:1404.1140, December 2014. Extended version of the published AAAI'15 paper including proofs.
    Details     Download: pdf [1.2MB]  
33. Frans A. Oliehoek, Shimon Whiteson, and Matthijs T. J. Spaan. Exploiting Agent and Type Independence in Collaborative Graphical Bayesian Games. ArXiv e-prints, arXiv:1108.0404, 2011. http://arxiv.org/abs/1108.0404
    Details     Download: pdf [661.1kB]  

Ph.D. Thesis

1. Frans A. Oliehoek. Value-Based Planning for Teams of Agents in Stochastic Partially Observable Environments. Ph.D. Thesis, Informatics Institute, University of Amsterdam, 2010.
   Details     Download: pdf [4.7MB]  

Master's Thesis

1. Frans A. Oliehoek. Game Theory and AI: a Unified Approach to Poker Games. Master's Thesis, University of Amsterdam,2005.
   Details     Download: pdf [2.5MB]  ps.gz [945.2kB]  

Other

1. Frans A. Oliehoek, Elena Congeduti, Aleksander Czechowski, Jinke He, Alexander Mey, Rolf A.N. Starre, and Miguel Suau. About `Influence'. Blog, 2022.
   https://www.fransoliehoek.net/wp/2022/02/01/a-blog-about-influence/
   Details     Download: pdf [408.4kB]  
2. Frans A. Oliehoek, Matthijs T. J. Spaan, Philipp Robbel, and João V. Messias. The MADP Toolbox 0.4, May 2016.
   Details     Download: pdf [1.2MB]  
3. Frans A. Oliehoek, Matthijs T. J. Spaan, Philipp Robbel, and João V. Messias. The MADP Toolbox 0.3.1, April 2015.
   Details     Download: pdf [898.3kB]  

Unspecified

1. Miguel Suau, Jinke He, Mustafa Mert Çelikok, Matthijs T. J. Spaan, and Frans A. Oliehoek. Distributed Influence-Augmented Local Simulators for Parallel MARL in Large Networked Systems. In Advances in Neural Information Processing Systems 35, December 2022.
   Details     Download: pdf [658.0kB]  
2. Aleksander Czechowski and Frans A. Oliehoek. Alternating Maximization with Behavioral Cloning. In Proceedings of the 32nd Benelux Conference on Artificial Intelligence (BNAIC) and the 29th Belgian Dutch Conference on Machine Learning (Benelearn), November 2020.
   Details     Download: pdf [223.2kB]  

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