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Frans A. Oliehoek
Frans Adriaan Oliehoek
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- affiliation: Delft University of Technology, The Netherlands
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2020 – today
- 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
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
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
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
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
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
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
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
A Sufficient Statistic for Influence in Structured Multiagent Environments. J. Artif. Intell. Res. 70: 789-870 (2021) - [j11]Christian Neumeyer
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
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
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
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
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
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
Learning From Demonstration in the Wild. ICRA 2019: 775-781 - [i20]Jacopo Castellini, Frans A. Oliehoek, Rahul Savani
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
Reports on the 2018 AAAI Spring Symposium Series. AI Mag. 39(4): 29-35 (2018) - [j8]Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek
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
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
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
Maximizing the Probability of Arriving on Time: A Practical Q-Learning Method. AAAI 2017: 4481-4487 - [c42]Frans A. Oliehoek
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
LiftUpp: Support to develop learner performance. CoRR abs/1704.06549 (2017) - [i12]Frans A. Oliehoek, Rahul Savani
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
The 2015 AAAI Fall Symposium Series Reports. AI Mag. 37(2): 85-90 (2016) - [j5]Christopher Amato
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
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
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
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
Incremental Clustering and Expansion for Faster Optimal Planning in Dec-POMDPs. J. Artif. Intell. Res. 46: 449-509 (2013) - [c19]Diederik M. Roijers
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
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
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
Q-value functions for decentralized POMDPs. AAMAS 2007: 220 - [c3]Frans A. Oliehoek
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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