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ORCIDFrans A. Oliehoek
Frans Adriaan Oliehoek
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- affiliation: Delft University of Technology, The Netherlands
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2020 – today
- 2025
[e1]Frans A. Oliehoek
, Manon Kok, Sicco Verwer:
Artificial Intelligence and Machine Learning - 35th Benelux Conference, BNAIC/Benelearn 2023, Delft, The Netherlands, November 8-10, 2023, Revised Selected Papers. Communications in Computer and Information Science 2187, Springer 2025, ISBN 978-3-031-74649-9 [contents]- 2024
- [j17]Raphaël Avalos, Eugenio Bargiacchi, Ann Nowé, Diederik M. Roijers, Frans A. Oliehoek:
Online Planning in POMDPs with State-Requests. RLJ 1: 108-129 (2024) - [j16]Miguel Suau, Matthijs T. J. Spaan, Frans A. Oliehoek:
Bad Habits: Policy Confounding and Out-of-Trajectory Generalization in RL. RLJ 4: 1711-1732 (2024) - [c82]Robert T. Loftin, Mustafa Mert Çelikok, Herke van Hoof, Samuel Kaski, Frans A. Oliehoek:
Uncoupled Learning of Differential Stackelberg Equilibria with Commitments. AAMAS 2024: 1265-1273 - [c81]Jinke He, Thomas M. Moerland, Joery A. de Vries, Frans A. Oliehoek:
What Model Does MuZero Learn? ECAI 2024: 1599-1606 - [c80]Zuzanna Osika, Jazmin Zatarain Salazar, Frans A. Oliehoek, Pradeep K. Murukannaiah:
Navigating Trade-offs: Policy Summarization for Multi-Objective Reinforcement Learning. ECAI 2024: 2919-2926 - [c79]Kata Naszádi, Frans A. Oliehoek, Christof Monz:
Communicating with Speakers and Listeners of Different Pragmatic Levels. EMNLP 2024: 21777-21783 - [c78]Ariyan Bighashdel, Yongzhao Wang, Stephen McAleer, Rahul Savani, Frans A. Oliehoek:
Policy Space Response Oracles: A Survey. IJCAI 2024: 7951-7961 - [i57]Jan Wehner, Frans A. Oliehoek, Luciano Cavalcante Siebert:
Explaining Learned Reward Functions with Counterfactual Trajectories. CoRR abs/2402.04856 (2024) - [i56]Davide Mambelli, Stephan Bongers, Onno Zoeter, Matthijs T. J. Spaan, Frans A. Oliehoek:
When Do Off-Policy and On-Policy Policy Gradient Methods Align? CoRR abs/2402.12034 (2024) - [i55]Ariyan Bighashdel, Yongzhao Wang, Stephen McAleer, Rahul Savani, Frans A. Oliehoek:
Policy Space Response Oracles: A Survey. CoRR abs/2403.02227 (2024) - [i54]Mustafa Mert Çelikok, Frans A. Oliehoek, Jan-Willem van de Meent:
Inverse Concave-Utility Reinforcement Learning is Inverse Game Theory. CoRR abs/2405.19024 (2024) - [i53]Raphaël Avalos, Eugenio Bargiacchi, Ann Nowé, Diederik M. Roijers, Frans A. Oliehoek:
Online Planning in POMDPs with State-Requests. CoRR abs/2407.18812 (2024) - [i52]Pengzhi Yang, Xinyu Wang, Ruipeng Zhang, Cong Wang, Frans A. Oliehoek, Jens Kober:
Task-unaware Lifelong Robot Learning with Retrieval-based Weighted Local Adaptation. CoRR abs/2410.02995 (2024) - [i51]Kata Naszádi, Frans A. Oliehoek, Christof Monz:
Communicating with Speakers and Listeners of Different Pragmatic Levels. CoRR abs/2410.05851 (2024) - 2023
- [j15]Shi Yuan Tang, Athirai A. Irissappane, Frans A. Oliehoek, Jie Zhang:
Teacher-apprentices RL (TARL): leveraging complex policy distribution through generative adversarial hypernetwork in reinforcement learning. Auton. Agents Multi Agent Syst. 37(2): 25 (2023) - [j14]Rolf A. N. Starre, Marco Loog, Elena Congeduti, Frans A. Oliehoek:
An Analysis of Model-Based Reinforcement Learning From Abstracted Observations. Trans. Mach. Learn. Res. 2023 (2023) - [c77]Aleksander Czechowski, Frans A. Oliehoek:
Safety Guarantees in Multi-agent Learning via Trapping Regions. AAMAS 2023: 2403-2405 - [c76]Aleksander Czechowski, Frans A. Oliehoek:
Safe Multi-agent Learning via Trapping Regions. IJCAI 2023: 82-90 - [c75]Zuzanna Osika, Jazmin Zatarain Salazar, Diederik M. Roijers, Frans A. Oliehoek, Pradeep K. Murukannaiah:
What Lies beyond the Pareto Front? A Survey on Decision-Support Methods for Multi-Objective Optimization. IJCAI 2023: 6741-6749 - [i50]Robert Tyler Loftin, Mustafa Mert Çelikok, Herke van Hoof, Samuel Kaski, Frans A. Oliehoek:
Uncoupled Learning of Differential Stackelberg Equilibria with Commitments. CoRR abs/2302.03438 (2023) - [i49]Aleksander Czechowski, Frans A. Oliehoek:
Safety Guarantees in Multi-agent Learning via Trapping Regions. CoRR abs/2302.13844 (2023) - [i48]Robert Tyler Loftin, Mustafa Mert Çelikok, Frans A. Oliehoek:
Towards a Unifying Model of Rationality in Multiagent Systems. CoRR abs/2305.18071 (2023) - [i47]Jinke He, Thomas M. Moerland, Frans A. Oliehoek:
What model does MuZero learn? CoRR abs/2306.00840 (2023) - [i46]Miguel Suau, Matthijs T. J. Spaan, Frans A. Oliehoek:
Bad Habits: Policy Confounding and Out-of-Trajectory Generalization in RL. CoRR abs/2306.02419 (2023) - [i45]Zuzanna Osika, Jazmin Zatarain Salazar, Diederik M. Roijers, Frans A. Oliehoek, Pradeep K. Murukannaiah:
What Lies beyond the Pareto Front? A Survey on Decision-Support Methods for Multi-Objective Optimization. CoRR abs/2311.11288 (2023) - 2022
- [c74]Mustafa Mert Çelikok, Frans A. Oliehoek, Samuel Kaski:
Best-Response Bayesian Reinforcement Learning with Bayes-adaptive POMDPs for Centaurs. AAMAS 2022: 235-243 - [c73]Sammie Katt, Hai Nguyen, Frans A. Oliehoek, Christopher Amato:
BADDr: Bayes-Adaptive Deep Dropout RL for POMDPs. AAMAS 2022: 723-731 - [c72]Markus Peschl, Arkady Zgonnikov, Frans A. Oliehoek, Luciano Cavalcante Siebert:
MORAL: Aligning AI with Human Norms through Multi-Objective Reinforced Active Learning. AAMAS 2022: 1038-1046 - [c71]Miguel Suau, Jinke He, Matthijs T. J. Spaan, Frans A. Oliehoek:
Speeding up Deep Reinforcement Learning through Influence-Augmented Local Simulators. AAMAS 2022: 1735-1737 - [c70]Rolf A. N. Starre, Marco Loog, Frans A. Oliehoek:
Model-Based Reinforcement Learning with State Abstraction: A Survey. BNAIC/BENELEARN 2022: 133-148 - [c69]Vibhav Inna Kedege, Aleksander Czechowski, Ludo Stellingwerff, Frans A. Oliehoek:
Multi Robot Surveillance and Planning in Limited Communication Environments. ICAART (1) 2022: 139-147 - [c68]Elise van der Pol, Herke van Hoof, Frans A. Oliehoek, Max Welling:
Multi-Agent MDP Homomorphic Networks. ICLR 2022 - [c67]Robert Tyler Loftin, Frans A. Oliehoek:
On the Impossibility of Learning to Cooperate with Adaptive Partner Strategies in Repeated Games. ICML 2022: 14197-14209 - [c66]Miguel Suau, Jinke He, Matthijs T. J. Spaan, Frans A. Oliehoek:
Influence-Augmented Local Simulators: a Scalable Solution for Fast Deep RL in Large Networked Systems. ICML 2022: 20604-20624 - [c65]Jinke He, Miguel Suau, Hendrik Baier, Michael Kaisers, Frans A. Oliehoek:
Online Planning in POMDPs with Self-Improving Simulators. IJCAI 2022: 4628-4634 - [c64]Miguel Suau, Jinke He, Mustafa Mert Çelikok, Matthijs T. J. Spaan, Frans A. Oliehoek:
Distributed Influence-Augmented Local Simulators for Parallel MARL in Large Networked Systems. NeurIPS 2022 - [i44]Markus Peschl, Arkady Zgonnikov, Frans A. Oliehoek, Luciano Cavalcante Siebert:
MORAL: Aligning AI with Human Norms through Multi-Objective Reinforced Active Learning. CoRR abs/2201.00012 (2022) - [i43]Jinke He, Miguel Suau, Hendrik Baier, Michael Kaisers, Frans A. Oliehoek:
Online Planning in POMDPs with Self-Improving Simulators. CoRR abs/2201.11404 (2022) - [i42]Miguel Suau, Jinke He, Matthijs T. J. Spaan, Frans A. Oliehoek:
Influence-Augmented Local Simulators: A Scalable Solution for Fast Deep RL in Large Networked Systems. CoRR abs/2202.01534 (2022) - [i41]Sammie Katt, Hai Nguyen, Frans A. Oliehoek, Christopher Amato:
BADDr: Bayes-Adaptive Deep Dropout RL for POMDPs. CoRR abs/2202.08884 (2022) - [i40]Mustafa Mert Çelikok, Frans A. Oliehoek, Samuel Kaski:
Best-Response Bayesian Reinforcement Learning with Bayes-adaptive POMDPs for Centaurs. CoRR abs/2204.01160 (2022) - [i39]Robert Tyler Loftin, Frans A. Oliehoek:
On the Impossibility of Learning to Cooperate with Adaptive Partner Strategies in Repeated Games. CoRR abs/2206.10614 (2022) - [i38]Miguel Suau, Jinke He, Mustafa Mert Çelikok, Matthijs T. J. Spaan, Frans A. Oliehoek:
Distributed Influence-Augmented Local Simulators for Parallel MARL in Large Networked Systems. CoRR abs/2207.00288 (2022) - [i37]Rolf A. N. Starre, Marco Loog, Frans A. Oliehoek:
An Analysis of Abstracted Model-Based Reinforcement Learning. CoRR abs/2208.14407 (2022) - 2021
- [j13]Jacopo Castellini, Frans A. Oliehoek, Rahul Savani, Shimon Whiteson:
Analysing factorizations of action-value networks for cooperative multi-agent reinforcement learning. Auton. Agents Multi Agent Syst. 35(2): 25 (2021) - [j12]Frans A. Oliehoek, Stefan J. Witwicki, Leslie Pack Kaelbling:
A Sufficient Statistic for Influence in Structured Multiagent Environments. J. Artif. Intell. Res. 70: 789-870 (2021) - [j11]Christian Neumeyer, Frans A. Oliehoek, Dariu M. Gavrila:
General-Sum Multi-Agent Continuous Inverse Optimal Control. IEEE Robotics Autom. Lett. 6(2): 3429-3436 (2021) - [c63]Canmanie T. Ponnambalam, Frans A. Oliehoek, Matthijs T. J. Spaan:
Abstraction-Guided Policy Recovery from Expert Demonstrations. ICAPS 2021: 560-568 - [c62]Alexander Mey, Frans A. Oliehoek:
Environment Shift Games: Are Multiple Agents the Solution, and not the Problem, to Non-Stationarity? AAMAS 2021: 23-27 - [c61]Elena Congeduti, Alexander Mey, Frans A. Oliehoek:
Loss Bounds for Approximate Influence-Based Abstraction. AAMAS 2021: 377-385 - [c60]Shi Yuan Tang, Athirai A. Irissappane, Frans A. Oliehoek, Jie Zhang:
Learning Complex Policy Distribution with CEM Guided Adversarial Hypernetwork. AAMAS 2021: 1308-1316 - [c59]Jacopo Castellini, Sam Devlin, Frans A. Oliehoek, Rahul Savani:
Difference Rewards Policy Gradients. AAMAS 2021: 1475-1477 - [c58]Burak Yildiz, Hayley Hung, Jesse H. Krijthe, Cynthia C. S. Liem, Marco Loog, Gosia Migut, Frans A. Oliehoek, Annibale Panichella, Przemyslaw Pawelczak, Stjepan Picek, Mathijs de Weerdt, Jan van Gemert:
ReproducedPapers.org: Openly Teaching and Structuring Machine Learning Reproducibility. RRPR 2021: 3-11 - [i36]Elise van der Pol, Herke van Hoof, Frans A. Oliehoek, Max Welling:
Multi-Agent MDP Homomorphic Networks. CoRR abs/2110.04495 (2021) - 2020
- [j10]Zeynep Akata, Dan Balliet, Maarten de Rijke, Frank Dignum, Virginia Dignum, Guszti Eiben, Antske Fokkens, Davide Grossi, Koen V. Hindriks, Holger H. Hoos, Hayley Hung, Catholijn M. Jonker, Christof Monz, Mark A. Neerincx, Frans A. Oliehoek, Henry Prakken, Stefan Schlobach, Linda C. van der Gaag, Frank van Harmelen, Herke van Hoof, Birna van Riemsdijk, Aimee van Wynsberghe, Rineke Verbrugge, Bart Verheij, Piek Vossen, Max Welling:
A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence. Computer 53(8): 18-28 (2020) - [c57]Yash Satsangi, Sungsu Lim, Shimon Whiteson, Frans A. Oliehoek, Martha White:
Maximizing Information Gain in Partially Observable Environments via Prediction Rewards. AAMAS 2020: 1215-1223 - [c56]Elise van der Pol, Thomas Kipf, Frans A. Oliehoek, Max Welling:
Plannable Approximations to MDP Homomorphisms: Equivariance under Actions. AAMAS 2020: 1431-1439 - [c55]Aleksander Czechowski, Frans A. Oliehoek:
Decentralized MCTS via Learned Teammate Models. IJCAI 2020: 81-88 - [c54]Flávia Alves, Martin Gairing, Frans A. Oliehoek, Thanh-Toan Do:
Sensor Data for Human Activity Recognition: Feature Representation and Benchmarking. IJCNN 2020: 1-8 - [c53]Jinke He, Miguel Suau, Frans A. Oliehoek:
Influence-Augmented Online Planning for Complex Environments. NeurIPS 2020 - [c52]Mikko Lauri, Frans A. Oliehoek:
Multi-agent active perception with prediction rewards. NeurIPS 2020 - [c51]Elise van der Pol, Daniel E. Worrall, Herke van Hoof, Frans A. Oliehoek, Max Welling:
MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning. NeurIPS 2020 - [i35]Elise van der Pol, Thomas N. Kipf, Frans A. Oliehoek, Max Welling:
Plannable Approximations to MDP Homomorphisms: Equivariance under Actions. CoRR abs/2002.11963 (2020) - [i34]Aleksander Czechowski, Frans A. Oliehoek:
Decentralized MCTS via Learned Teammate Models. CoRR abs/2003.08727 (2020) - [i33]João P. Abrantes, Arnaldo J. Abrantes, Frans A. Oliehoek:
Mimicking Evolution with Reinforcement Learning. CoRR abs/2004.00048 (2020) - [i32]Christian Muench, Frans A. Oliehoek, Dariu M. Gavrila:
Diversity in Action: General-Sum Multi-Agent Continuous Inverse Optimal Control. CoRR abs/2004.12678 (2020) - [i31]Yash Satsangi, Sungsu Lim, Shimon Whiteson, Frans A. Oliehoek, Martha White:
Maximizing Information Gain in Partially Observable Environments via Prediction Reward. CoRR abs/2005.04912 (2020) - [i30]Flávia Alves, Martin Gairing, Frans A. Oliehoek, Thanh-Toan Do:
Sensor Data for Human Activity Recognition: Feature Representation and Benchmarking. CoRR abs/2005.07308 (2020) - [i29]Elise van der Pol, Daniel E. Worrall, Herke van Hoof, Frans A. Oliehoek, Max Welling:
MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning. CoRR abs/2006.16908 (2020) - [i28]Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek, Matthijs T. J. Spaan:
Exploiting Submodular Value Functions For Scaling Up Active Perception. CoRR abs/2009.09696 (2020) - [i27]Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek, Henri Bouma:
Real-Time Resource Allocation for Tracking Systems. CoRR abs/2010.03024 (2020) - [i26]Jinke He, Miguel Suau, Frans A. Oliehoek:
Influence-Augmented Online Planning for Complex Environments. CoRR abs/2010.11038 (2020) - [i25]Mikko Lauri, Frans A. Oliehoek:
Multi-agent active perception with prediction rewards. CoRR abs/2010.11835 (2020) - [i24]Elena Congeduti, Alexander Mey, Frans A. Oliehoek:
Loss Bounds for Approximate Influence-Based Abstraction. CoRR abs/2011.01788 (2020) - [i23]Wook Lee, Frans A. Oliehoek:
Analog Circuit Design with Dyna-Style Reinforcement Learning. CoRR abs/2011.07665 (2020) - [i22]Burak Yildiz, Hayley Hung, Jesse H. Krijthe, Cynthia C. S. Liem, Marco Loog, Gosia Migut, Frans A. Oliehoek, Annibale Panichella, Przemyslaw Pawelczak, Stjepan Picek, Mathijs de Weerdt, Jan van Gemert:
ReproducedPapers.org: Openly teaching and structuring machine learning reproducibility. CoRR abs/2012.01172 (2020) - [i21]Jacopo Castellini, Sam Devlin, Frans A. Oliehoek, Rahul Savani:
Difference Rewards Policy Gradients. CoRR abs/2012.11258 (2020)
2010 – 2019
- 2019
- [c50]Sammie Katt, Frans A. Oliehoek, Christopher Amato:
Bayesian Reinforcement Learning in Factored POMDPs. AAMAS 2019: 7-15 - [c49]Jacopo Castellini, Frans A. Oliehoek, Rahul Savani, Shimon Whiteson:
The Representational Capacity of Action-Value Networks for Multi-Agent Reinforcement Learning. AAMAS 2019: 1862-1864 - [c48]Sammie Katt, Frans A. Oliehoek, Chris Amato:
Bayesian RL in Factored POMDPs. BNAIC/BENELEARN 2019 - [c47]Feryal M. P. Behbahani, Kyriacos Shiarlis, Xi Chen, Vitaly Kurin, Sudhanshu Kasewa, Ciprian Stirbu, João Gomes, Supratik Paul, Frans A. Oliehoek, João V. Messias, Shimon Whiteson:
Learning From Demonstration in the Wild. ICRA 2019: 775-781 - [i20]Jacopo Castellini, Frans A. Oliehoek, Rahul Savani, Shimon Whiteson:
The Representational Capacity of Action-Value Networks for Multi-Agent Reinforcement Learning. CoRR abs/1902.07497 (2019) - [i19]Frans A. Oliehoek, Stefan J. Witwicki, Leslie Pack Kaelbling:
A Sufficient Statistic for Influence in Structured Multiagent Environments. CoRR abs/1907.09278 (2019) - [i18]Miguel Suau, Elena Congeduti, Rolf Starre, Aleksander Czechowski, Frans A. Oliehoek:
Influence-aware Memory for Deep Reinforcement Learning. CoRR abs/1911.07643 (2019) - 2018
- [j9]Christopher Amato, Haitham Bou-Ammar, Elizabeth F. Churchill, Erez Karpas, Takashi Kido, Mike Kuniavsky, William F. Lawless, Francesca Rossi, Frans A. Oliehoek, Stephen Russell, Keiki Takadama, Siddharth Srivastava, Karl Tuyls, Philip van Allen, Kristen Brent Venable, Peter Vrancx, Shiqi Zhang:
Reports on the 2018 AAAI Spring Symposium Series. AI Mag. 39(4): 29-35 (2018) - [j8]Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek, Matthijs T. J. Spaan:
Exploiting submodular value functions for scaling up active perception. Auton. Robots 42(2): 209-233 (2018) - [c46]Richard Klíma, Karl Tuyls, Frans A. Oliehoek:
Model-Based Reinforcement Learning under Periodical Observability. AAAI Spring Symposia 2018 - [c45]Frans A. Oliehoek, Rahul Savani, Jose Gallego-Posada, Elise van der Pol, Roderich Groß:
Beyond Local Nash Equilibria for Adversarial Networks. BNCAI 2018: 73-89 - [c44]Frans A. Oliehoek:
Interactive Learning and Decision Making: Foundations, Insights & Challenges. IJCAI 2018: 5703-5708 - [i17]Sammie Katt, Frans A. Oliehoek, Christopher Amato:
Learning in POMDPs with Monte Carlo Tree Search. CoRR abs/1806.05631 (2018) - [i16]Frans A. Oliehoek, Rahul Savani, Jose Gallego-Posada, Elise van der Pol, Roderich Groß:
Beyond Local Nash Equilibria for Adversarial Networks. CoRR abs/1806.07268 (2018) - [i15]Feryal M. P. Behbahani, Kyriacos Shiarlis, Xi Chen, Vitaly Kurin, Sudhanshu Kasewa, Ciprian Stirbu, João Gomes, Supratik Paul, Frans A. Oliehoek, João V. Messias, Shimon Whiteson:
Learning from Demonstration in the Wild. CoRR abs/1811.03516 (2018) - [i14]Sammie Katt, Frans A. Oliehoek, Christopher Amato:
Bayesian Reinforcement Learning in Factored POMDPs. CoRR abs/1811.05612 (2018) - 2017
- [j7]Frans A. Oliehoek, Matthijs T. J. Spaan, Bas Terwijn, Philipp Robbel, João V. Messias:
The MADP Toolbox: An Open Source Library for Planning and Learning in (Multi-)Agent Systems. J. Mach. Learn. Res. 18: 89:1-89:5 (2017) - [c43]Zhiguang Cao, Hongliang Guo, Jie Zhang, Frans A. Oliehoek, Ulrich Fastenrath:
Maximizing the Probability of Arriving on Time: A Practical Q-Learning Method. AAAI 2017: 4481-4487 - [c42]Frans A. Oliehoek, Rahul Savani, Elliot Adderton, Xia Cui, David Jackson, Phil Jimmieson, John Christopher Jones, Keith Kennedy, Ben Mason, Adam Plumbley, Luke Dawson:
LiftUpp: Support to Develop Learner Performance. AIED 2017: 553-556 - [c41]Daniel Claes, Frans A. Oliehoek, Hendrik Baier, Karl Tuyls:
Decentralised Online Planning for Multi-Robot Warehouse Commissioning. AAMAS 2017: 492-500 - [c40]Sammie Katt, Frans A. Oliehoek, Christopher Amato:
Learning in POMDPs with Monte Carlo Tree Search. ICML 2017: 1819-1827 - [c39]Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek, Henri Bouma:
Real-Time Resource Allocation for Tracking Systems. UAI 2017 - [i13]Frans A. Oliehoek, Rahul Savani, Elliot Adderton, Xia Cui, David Jackson, Phil Jimmieson, John Christopher Jones, Keith Kennedy, Ben Mason, Adam Plumbley, Luke Dawson:
LiftUpp: Support to develop learner performance. CoRR abs/1704.06549 (2017) - [i12]Frans A. Oliehoek, Rahul Savani, Jose Gallego-Posada, Elise van der Pol, Edwin D. de Jong, Roderich Gross:
GANGs: Generative Adversarial Network Games. CoRR abs/1712.00679 (2017) - 2016
- [b1]Frans A. Oliehoek, Christopher Amato:
A Concise Introduction to Decentralized POMDPs. Springer Briefs in Intelligent Systems, Springer 2016, ISBN 978-3-319-28927-4, pp. 1-116 - [j6]Nisar Ahmed, Paul Bello, Selmer Bringsjord, Micah Clark, Bradley Hayes, Christopher Miller, Frans A. Oliehoek, Frank Stein, Matthijs T. J. Spaan:
The 2015 AAAI Fall Symposium Series Reports. AI Mag. 37(2): 85-90 (2016) - [j5]Christopher Amato, Ofra Amir, Joanna Bryson, Barbara J. Grosz, Bipin Indurkhya, Emre Kiciman, Takashi Kido, William F. Lawless, Miao Liu, Braden McDorman, Ross Mead, Frans A. Oliehoek, Andrew Specian, Georgi Stojanov, Keiki Takadama:
Reports of the AAAI 2016 Spring Symposium Series. AI Mag. 37(4): 83-88 (2016) - [c38]Athirai Aravazhi Irissappane, Frans A. Oliehoek, Jie Zhang:
A Scalable Framework to Choose Sellers in E-Marketplaces Using POMDPs. AAAI 2016: 158-164 - [c37]Philipp Robbel, Frans A. Oliehoek, Mykel J. Kochenderfer:
Exploiting Anonymity in Approximate Linear Programming: Scaling to Large Multiagent MDPs. AAAI 2016: 2537-2543 - [c36]Joris Scharpff, Diederik M. Roijers, Frans A. Oliehoek, Matthijs T. J. Spaan, Mathijs Michiel de Weerdt:
Solving Transition-Independent Multi-Agent MDPs with Sparse Interactions. AAAI 2016: 3174-3180 - [c35]Timon V. Kanters, Frans A. Oliehoek, Michael Kaisers, Stan R. van den Bosch, Joep Grispen, Jeroen Hermans:
Energy- and Cost-Efficient Pumping Station Control. AAAI 2016: 3842-3848 - [c34]Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek:
Probably Approximately Correct Greedy Maximization: (Extended Abstract). AAMAS 2016: 1387-1388 - [c33]Auke J. Wiggers, Frans A. Oliehoek, Diederik M. Roijers:
Structure in the Value Function of Two-Player Zero-Sum Games of Incomplete Information. ECAI 2016: 1628-1629 - [c32]Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek:
PAC Greedy Maximization with Efficient Bounds on Information Gain for Sensor Selection. IJCAI 2016: 3220-3227 - [i11]Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek:
Probably Approximately Correct Greedy Maximization. CoRR abs/1602.07860 (2016) - [i10]Auke J. Wiggers, Frans A. Oliehoek, Diederik M. Roijers:
Structure in the Value Function of Two-Player Zero-Sum Games of Incomplete Information. CoRR abs/1606.06888 (2016) - 2015
- [j4]Diederik Marijn Roijers, Shimon Whiteson, Frans A. Oliehoek:
Computing Convex Coverage Sets for Faster Multi-objective Coordination. J. Artif. Intell. Res. 52: 399-443 (2015) - [c31]Christopher Amato, Frans A. Oliehoek:
Scalable Planning and Learning for Multiagent POMDPs. AAAI 2015: 1995-2002 - [c30]Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek:
Exploiting Submodular Value Functions for Faster Dynamic Sensor Selection. AAAI 2015: 3356-3363 - [c29]Frans A. Oliehoek, Matthijs T. J. Spaan, Philipp Robbel, João V. Messias:
The MADP Toolbox: An Open-Source Library for Planning and Learning in (Multi-)Agent Systems. AAAI Fall Symposia 2015: 59-62 - [c28]Philipp Robbel, Frans A. Oliehoek, Mykel J. Kochenderfer:
Exploiting Anonymity in Approximate Linear Programming: Scaling to Large Multiagent MDPs. AAAI Fall Symposia 2015: 75-82 - [c27]Daniel Claes, Philipp Robbel, Frans A. Oliehoek, Karl Tuyls, Daniel Hennes, Wiebe van der Hoek:
Effective Approximations for Multi-Robot Coordination in Spatially Distributed Tasks. AAMAS 2015: 881-890 - [c26]Frans A. Oliehoek, Matthijs T. J. Spaan, Stefan J. Witwicki:
Influence-Optimistic Local Values for Multiagent Planning. AAMAS 2015: 1703-1704 - [c25]Frans Adriaan Oliehoek, Matthijs T. J. Spaan, Stefan J. Witwicki:
Factored Upper Bounds for Multiagent Planning Problems under Uncertainty with Non-Factored Value Functions. IJCAI 2015: 1645-1651 - [c24]Diederik Marijn Roijers, Shimon Whiteson, Frans A. Oliehoek:
Point-Based Planning for Multi-Objective POMDPs. IJCAI 2015: 1666-1672 - [c23]Athirai Aravazhi Irissappane, Jie Zhang, Frans A. Oliehoek, Partha Sarathi Dutta:
Secure Routing in Wireless Sensor Networks via POMDPs. IJCAI 2015: 2617-2623 - [p3]Julia Efremova, Bijan Ranjbar Sahraei, Hossein Rahmani, Frans A. Oliehoek, Toon Calders, Karl Tuyls, Gerhard Weiss:
Multi-Source Entity Resolution for Genealogical Data. Population Reconstruction 2015: 129-154 - [i9]Frans A. Oliehoek, Matthijs T. J. Spaan, Stefan J. Witwicki:
Influence-Optimistic Local Values for Multiagent Planning - Extended Version. CoRR abs/1502.05443 (2015) - [i8]Joris Scharpff, Diederik M. Roijers, Frans A. Oliehoek, Matthijs T. J. Spaan, Mathijs de Weerdt:
Solving Transition-Independent Multi-agent MDPs with Sparse Interactions (Extended version). CoRR abs/1511.09047 (2015) - [i7]Philipp Robbel, Frans A. Oliehoek, Mykel J. Kochenderfer:
Exploiting Anonymity in Approximate Linear Programming: Scaling to Large Multiagent MDPs (Extended Version). CoRR abs/1511.09080 (2015) - [i6]Athirai Aravazhi Irissappane, Frans A. Oliehoek, Jie Zhang:
Scaling POMDPs For Selecting Sellers in E-markets-Extended Version. CoRR abs/1511.09147 (2015) - 2014
- [c22]Diederik Marijn Roijers, Joris Scharpff, Matthijs T. J. Spaan, Frans A. Oliehoek, Mathijs de Weerdt, Shimon Whiteson:
Bounded Approximations for Linear Multi-Objective Planning Under Uncertainty. ICAPS 2014 - [c21]Diederik M. Roijers, Shimon Whiteson, Frans A. Oliehoek:
Linear support for multi-objective coordination graphs. AAMAS 2014: 1297-1304 - [c20]Athirai Aravazhi Irissappane, Frans A. Oliehoek, Jie Zhang:
A POMDP based approach to optimally select sellers in electronic marketplaces. AAMAS 2014: 1329-1336 - [i5]Frans Adriaan Oliehoek, Matthijs T. J. Spaan, Christopher Amato, Shimon Whiteson:
Incremental Clustering and Expansion for Faster Optimal Planning in Dec-POMDPs. CoRR abs/1402.0566 (2014) - [i4]Christopher Amato, Frans A. Oliehoek:
Scalable Planning and Learning for Multiagent POMDPs. CoRR abs/1404.1140 (2014) - 2013
- [j3]Frans A. Oliehoek, Matthijs T. J. Spaan, Christopher Amato, Shimon Whiteson:
Incremental Clustering and Expansion for Faster Optimal Planning in Dec-POMDPs. J. Artif. Intell. Res. 46: 449-509 (2013) - [c19]Diederik M. Roijers, Shimon Whiteson, Frans A. Oliehoek:
Computing Convex Coverage Sets for Multi-objective Coordination Graphs. ADT 2013: 309-323 - [c18]Frans A. Oliehoek, Shimon Whiteson, Matthijs T. J. Spaan:
Approximate solutions for factored Dec-POMDPs with many agents. AAMAS 2013: 563-570 - [c17]Diederik M. Roijers, Shimon Whiteson, Frans A. Oliehoek:
Multi-objective variable elimination for collaborative graphical games. AAMAS 2013: 1209-1210 - [c16]Frans Adriaan Oliehoek:
Sufficient Plan-Time Statistics for Decentralized POMDPs. IJCAI 2013: 302-308 - 2012
- [c15]Frans Adriaan Oliehoek, Matthijs T. J. Spaan:
Tree-Based Solution Methods for Multiagent POMDPs with Delayed Communication. AAAI 2012: 1415-1421 - [c14]Frans Adriaan Oliehoek, Stefan J. Witwicki, Leslie Pack Kaelbling:
Influence-Based Abstraction for Multiagent Systems. AAAI 2012: 1422-1428 - [c13]Stefan J. Witwicki, Frans A. Oliehoek, Leslie Pack Kaelbling:
Heuristic search of multiagent influence space. AAMAS 2012: 973-980 - [c12]Frans A. Oliehoek, Matthijs T. J. Spaan:
Tree-based pruning for multiagent POMDPs with delayed communication. AAMAS 2012: 1229-1230 - [c11]Frans A. Oliehoek, Shimon Whiteson, Matthijs T. J. Spaan:
Exploiting Structure in Cooperative Bayesian Games. UAI 2012: 654-665 - [p2]Frans A. Oliehoek:
Decentralized POMDPs. Reinforcement Learning 2012: 471-503 - [i3]Frans A. Oliehoek, Shimon Whiteson, Matthijs T. J. Spaan:
Exploiting Structure in Cooperative Bayesian Games. CoRR abs/1210.4886 (2012) - 2011
- [c10]Matthijs T. J. Spaan, Frans A. Oliehoek, Christopher Amato:
Scaling Up Optimal Heuristic Search in Dec-POMDPs via Incremental Expansion. IJCAI 2011: 2027-2032 - [i2]Frans A. Oliehoek, Shimon Whiteson, Matthijs T. J. Spaan:
Exploiting Agent and Type Independence in Collaborative Graphical Bayesian Games. CoRR abs/1108.0404 (2011) - [i1]Frans A. Oliehoek, Matthijs T. J. Spaan, Nikos Vlassis:
Optimal and Approximate Q-value Functions for Decentralized POMDPs. CoRR abs/1111.0062 (2011) - 2010
- [c9]Frans A. Oliehoek, Matthijs T. J. Spaan, Jilles Steeve Dibangoye, Christopher Amato:
Heuristic search for identical payoff Bayesian games. AAMAS 2010: 1115-1122 - [p1]Frans A. Oliehoek, Arnoud Visser:
A Decision-Theoretic Approach to Collaboration: Principal Description Methods and Efficient Heuristic Approximations. Interactive Collaborative Information Systems 2010: 87-124
2000 – 2009
- 2009
- [c8]Frans A. Oliehoek, Shimon Whiteson, Matthijs T. J. Spaan:
Lossless clustering of histories in decentralized POMDPs. AAMAS (1) 2009: 577-584 - 2008
- [j2]Frans A. Oliehoek, Julian F. P. Kooij, Nikos Vlassis:
The Cross-Entropy Method for Policy Search in Decentralized POMDPs. Informatica (Slovenia) 32(4): 341-357 (2008) - [j1]Frans A. Oliehoek, Matthijs T. J. Spaan, Nikos Vlassis:
Optimal and Approximate Q-value Functions for Decentralized POMDPs. J. Artif. Intell. Res. 32: 289-353 (2008) - [c7]Matthijs T. J. Spaan, Frans A. Oliehoek, Nikos Vlassis:
Multiagent Planning Under Uncertainty with Stochastic Communication Delays. ICAPS 2008: 338-345 - [c6]Frans A. Oliehoek, Matthijs T. J. Spaan, Shimon Whiteson, Nikos Vlassis:
Exploiting locality of interaction in factored Dec-POMDPs. AAMAS (1) 2008: 517-524 - 2007
- [c5]Frans A. Oliehoek, Nikos Vlassis:
Q-value Heuristics for Approximate Solutions of Dec-POMDPs. AAAI Spring Symposium: Game Theoretic and Decision Theoretic Agents 2007: 31-37 - [c4]Frans A. Oliehoek, Nikos Vlassis:
Q-value functions for decentralized POMDPs. AAMAS 2007: 220 - [c3]Frans A. Oliehoek, Julian F. P. Kooij, Nikos Vlassis:
A Cross-Entropy Approach to Solving Dec-POMDPs. IDC 2007: 145-154 - 2006
- [c2]Frans A. Oliehoek, Edwin D. de Jong, Nikos Vlassis:
The parallel Nash Memory for asymmetric games. GECCO 2006: 337-344 - 2005
- [c1]Frans A. Oliehoek, Nikos Vlassis, Edwin D. de Jong:
Coevolutionary Nash in poker games. BNAIC 2005: 188-193
Coauthor Index
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