Coevolutionary Nash in poker games. - Frans A. Oliehoek; Nikos Vlassis; Edwin D. de Jong (BNAIC, 2005)

The parallel Nash Memory for asymmetric games. - Frans A. Oliehoek; Edwin D. de Jong; Nikos Vlassis (GECCO, 2006)

Q-value Heuristics for Approximate Solutions of Dec-POMDPs. - Frans A. Oliehoek; Nikos Vlassis (AAAI Spring Symposium: Game Theoretic and Decision Theoretic Agents, 2007)

Q-value functions for decentralized POMDPs. - Frans A. Oliehoek; Nikos Vlassis (AAMAS, 2007)

A Cross-Entropy Approach to Solving Dec-POMDPs. - Frans A. Oliehoek; Julian F. P. Kooij; Nikos Vlassis (IDC, 2007)

Multiagent Planning Under Uncertainty with Stochastic Communication Delays. - Matthijs T. J. Spaan; Frans A. Oliehoek; Nikos Vlassis (ICAPS, 2008)

Exploiting locality of interaction in factored Dec-POMDPs. - Frans A. Oliehoek; Matthijs T. J. Spaan; Shimon Whiteson; Nikos Vlassis (AAMAS (1), 2008)

The Cross-Entropy Method for Policy Search in Decentralized POMDPs. - Frans A. Oliehoek; Julian F. P. Kooij; Nikos Vlassis (Informatica (Slovenia), 2008)

Optimal and Approximate Q-value Functions for Decentralized POMDPs. - Frans A. Oliehoek; Matthijs T. J. Spaan; Nikos Vlassis (J. Artif. Intell. Res., 2008)

Lossless clustering of histories in decentralized POMDPs. - Frans A. Oliehoek; Shimon Whiteson; Matthijs T. J. Spaan (AAMAS (1), 2009)

Heuristic search for identical payoff Bayesian games. - Frans A. Oliehoek; Matthijs T. J. Spaan; Jilles Steeve Dibangoye; Christopher Amato (AAMAS, 2010)

A Decision-Theoretic Approach to Collaboration: Principal Description Methods and Efficient Heuristic Approximations. - Frans A. Oliehoek; Arnoud Visser (Interactive Collaborative Information Systems, 2010)

Scaling Up Optimal Heuristic Search in Dec-POMDPs via Incremental Expansion. - Matthijs T. J. Spaan; Frans A. Oliehoek; Christopher Amato (IJCAI, 2011)

Exploiting Agent and Type Independence in Collaborative Graphical Bayesian Games - Frans A. Oliehoek; Shimon Whiteson; Matthijs T. J. Spaan (CoRR, 2011)

Decentralized POMDPs. - Frans A. Oliehoek (Reinforcement Learning, 2012)

Tree-Based Solution Methods for Multiagent POMDPs with Delayed Communication. - Frans Adriaan Oliehoek; Matthijs T. J. Spaan (AAAI, 2012)

Influence-Based Abstraction for Multiagent Systems. - Frans Adriaan Oliehoek; Stefan J. Witwicki; Leslie Pack Kaelbling (AAAI, 2012)

Tree-based pruning for multiagent POMDPs with delayed communication. - Frans A. Oliehoek; Matthijs T. J. Spaan (AAMAS, 2012)

Heuristic search of multiagent influence space. - Stefan J. Witwicki; Frans A. Oliehoek; Leslie Pack Kaelbling (AAMAS, 2012)

Exploiting Structure in Cooperative Bayesian Games. - Frans A. Oliehoek; Shimon Whiteson; Matthijs T. J. Spaan (UAI, 2012)

Computing Convex Coverage Sets for Multi-objective Coordination Graphs. - Diederik M. Roijers; Shimon Whiteson; Frans A. Oliehoek (ADT, 2013)

Approximate solutions for factored Dec-POMDPs with many agents. - Frans A. Oliehoek; Shimon Whiteson; Matthijs T. J. Spaan (AAMAS, 2013)

Multi-objective variable elimination for collaborative graphical games. - Diederik M. Roijers; Shimon Whiteson; Frans A. Oliehoek (AAMAS, 2013)

Sufficient Plan-Time Statistics for Decentralized POMDPs. - Frans Adriaan Oliehoek (IJCAI, 2013)

Incremental Clustering and Expansion for Faster Optimal Planning in Dec-POMDPs. - Frans A. Oliehoek; Matthijs T. J. Spaan; Christopher Amato; Shimon Whiteson (J. Artif. Intell. Res., 2013)

Bounded Approximations for Linear Multi-Objective Planning Under Uncertainty. - Diederik Marijn Roijers; Joris Scharpff; Matthijs T. J. Spaan; Frans A. Oliehoek; Mathijs de Weerdt; Shimon Whiteson (ICAPS, 2014)

A POMDP based approach to optimally select sellers in electronic marketplaces. - Athirai Aravazhi Irissappane; Frans A. Oliehoek; Jie Zhang 002 (AAMAS, 2014)

Linear support for multi-objective coordination graphs. - Diederik M. Roijers; Shimon Whiteson; Frans A. Oliehoek (AAMAS, 2014)

Multi-Source Entity Resolution for Genealogical Data. - Julia Efremova; Bijan Ranjbar Sahraei; Hossein Rahmani 002; Frans A. Oliehoek; Toon Calders; Karl Tuyls; Gerhard Weiss 001 (Population Reconstruction, 2015)

Scalable Planning and Learning for Multiagent POMDPs. - Christopher Amato; Frans A. Oliehoek (AAAI, 2015)

Exploiting Submodular Value Functions for Faster Dynamic Sensor Selection. - Yash Satsangi; Shimon Whiteson; Frans A. Oliehoek (AAAI, 2015)

The MADP Toolbox: An Open-Source Library for Planning and Learning in (Multi-)Agent Systems. - Frans A. Oliehoek; Matthijs T. J. Spaan; Philipp Robbel; João V. Messias (AAAI Fall Symposia, 2015)

Effective Approximations for Multi-Robot Coordination in Spatially Distributed Tasks. - Daniel Claes; Philipp Robbel; Frans A. Oliehoek; Karl Tuyls; Daniel Hennes; Wiebe van der Hoek (AAMAS, 2015)

Influence-Optimistic Local Values for Multiagent Planning. - Frans A. Oliehoek; Matthijs T. J. Spaan; Stefan J. Witwicki (AAMAS, 2015)

Secure Routing in Wireless Sensor Networks via POMDPs. - Athirai Aravazhi Irissappane; Jie Zhang 002; Frans A. Oliehoek; Partha Sarathi Dutta (IJCAI, 2015)

Factored Upper Bounds for Multiagent Planning Problems under Uncertainty with Non-Factored Value Functions. - Frans Adriaan Oliehoek; Matthijs T. J. Spaan; Stefan J. Witwicki (IJCAI, 2015)

Point-Based Planning for Multi-Objective POMDPs. - Diederik Marijn Roijers; Shimon Whiteson; Frans A. Oliehoek (IJCAI, 2015)

Scaling POMDPs For Selecting Sellers in E-markets-Extended Version. - Athirai Aravazhi Irissappane; Frans A. Oliehoek; Jie Zhang 002 (CoRR, 2015)

Influence-Optimistic Local Values for Multiagent Planning - Extended Version. - Frans A. Oliehoek; Matthijs T. J. Spaan; Stefan J. Witwicki (CoRR, 2015)

Exploiting Anonymity in Approximate Linear Programming: Scaling to Large Multiagent MDPs (Extended Version). - Philipp Robbel; Frans A. Oliehoek; Mykel J. Kochenderfer (CoRR, 2015)

Solving Transition-Independent Multi-agent MDPs with Sparse Interactions (Extended version). - Joris Scharpff; Diederik M. Roijers; Frans A. Oliehoek; Matthijs T. J. Spaan; Mathijs de Weerdt (CoRR, 2015)

Computing Convex Coverage Sets for Faster Multi-objective Coordination. - Diederik Marijn Roijers; Shimon Whiteson; Frans A. Oliehoek (J. Artif. Intell. Res., 2015)

A Scalable Framework to Choose Sellers in E-Marketplaces Using POMDPs. - Athirai Aravazhi Irissappane; Frans A. Oliehoek; Jie Zhang 002 (AAAI, 2016)

Energy- and Cost-Efficient Pumping Station Control. - Timon V. Kanters; Frans A. Oliehoek; Michael Kaisers; Stan R. van den Bosch; Joep Grispen; Jeroen Hermans (AAAI, 2016)

Exploiting Anonymity in Approximate Linear Programming: Scaling to Large Multiagent MDPs. - Philipp Robbel; Frans A. Oliehoek; Mykel J. Kochenderfer (AAAI, 2016)

Solving Transition-Independent Multi-Agent MDPs with Sparse Interactions. - Joris Scharpff; Diederik M. Roijers; Frans A. Oliehoek; Matthijs T. J. Spaan; Mathijs Michiel de Weerdt (AAAI, 2016)

Probably Approximately Correct Greedy Maximization: (Extended Abstract). - Yash Satsangi; Shimon Whiteson; Frans A. Oliehoek (AAMAS, 2016)

Structure in the Value Function of Two-Player Zero-Sum Games of Incomplete Information. - Auke J. Wiggers; Frans A. Oliehoek; Diederik M. Roijers (ECAI, 2016)

PAC Greedy Maximization with Efficient Bounds on Information Gain for Sensor Selection. - Yash Satsangi; Shimon Whiteson; Frans A. Oliehoek (IJCAI, 2016)

The 2015 AAAI Fall Symposium Series Reports. - Nisar Ahmed; Paul Bello; Selmer Bringsjord; Micah Clark; Bradley Hayes; Christopher Miller; Frans A. Oliehoek; Frank Stein; Matthijs T. J. Spaan (AI Mag., 2016)

Reports of the AAAI 2016 Spring Symposium Series. - Christopher Amato; Ofra Amir; Joanna Bryson; Barbara J. Grosz; Bipin Indurkhya; Emre Kiciman; Takashi Kido; William F. Lawless; Miao Liu 001; Braden McDorman; Ross Mead; Frans A. Oliehoek; et al. (AI Mag., 2016)

Probably Approximately Correct Greedy Maximization. - Yash Satsangi; Shimon Whiteson; Frans A. Oliehoek (CoRR, 2016)

A Concise Introduction to Decentralized POMDPs - Frans A. Oliehoek; Christopher Amato (Springer, 2016)

Maximizing the Probability of Arriving on Time: A Practical Q-Learning Method. - Zhiguang Cao; Hongliang Guo; Jie Zhang 002; Frans A. Oliehoek; Ulrich Fastenrath (AAAI, 2017)

LiftUpp: Support to Develop Learner Performance. - Frans A. Oliehoek; Rahul Savani; Elliot Adderton; Xia Cui; David Jackson; Phil Jimmieson; John Christopher Jones; Keith Kennedy; Ben Mason; Adam Plumbley; Luke Dawson (AIED, 2017)

Decentralised Online Planning for Multi-Robot Warehouse Commissioning. - Daniel Claes; Frans A. Oliehoek; Hendrik Baier; Karl Tuyls (AAMAS, 2017)

Learning in POMDPs with Monte Carlo Tree Search. - Sammie Katt; Frans A. Oliehoek; Christopher Amato (ICML, 2017)

Real-Time Resource Allocation for Tracking Systems. - Yash Satsangi; Shimon Whiteson; Frans A. Oliehoek; Henri Bouma (UAI, 2017)

GANGs: Generative Adversarial Network Games. - Frans A. Oliehoek; Rahul Savani; Jose Gallego-Posada; Elise van der Pol; Edwin D. de Jong; Roderich Gross (CoRR, 2017)

The MADP Toolbox: An Open Source Library for Planning and Learning in (Multi-)Agent Systems. - Frans A. Oliehoek; Matthijs T. J. Spaan; Bas Terwijn; Philipp Robbel; João V. Messias (J. Mach. Learn. Res., 2017)

Model-Based Reinforcement Learning under Periodical Observability. - Richard Klíma; Karl Tuyls; Frans A. Oliehoek (AAAI Spring Symposia, 2018)

Beyond Local Nash Equilibria for Adversarial Networks. - Frans A. Oliehoek; Rahul Savani; Jose Gallego-Posada; Elise van der Pol; Roderich Groß (BNCAI, 2018)

Interactive Learning and Decision Making: Foundations, Insights & Challenges. - Frans A. Oliehoek (IJCAI, 2018)

Reports on the 2018 AAAI Spring Symposium Series. - Christopher Amato; Haitham Bou-Ammar; Elizabeth F. Churchill; Erez Karpas; Takashi Kido; Mike Kuniavsky; William F. Lawless; Francesca Rossi 001; Frans A. Oliehoek; Stephen Russell 001; Keiki Takadama; Siddharth Srivastava 001; et al. (AI Mag., 2018)

Exploiting submodular value functions for scaling up active perception. - Yash Satsangi; Shimon Whiteson; Frans A. Oliehoek; Matthijs T. J. Spaan (Auton. Robots, 2018)

The Representational Capacity of Action-Value Networks for Multi-Agent Reinforcement Learning. - Jacopo Castellini; Frans A. Oliehoek; Rahul Savani; Shimon Whiteson (AAMAS, 2019)

Bayesian Reinforcement Learning in Factored POMDPs. - Sammie Katt; Frans A. Oliehoek; Christopher Amato (AAMAS, 2019)

Bayesian RL in Factored POMDPs. - Sammie Katt; Frans A. Oliehoek; Chris Amato (BNAIC/BENELEARN, 2019)

Learning From Demonstration in the Wild. - 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 (ICRA, 2019)

Influence-aware Memory for Deep Reinforcement Learning. - Miguel Suau; Elena Congeduti; Rolf Starre; Aleksander Czechowski; Frans A. Oliehoek (CoRR, 2019)

Plannable Approximations to MDP Homomorphisms: Equivariance under Actions. - Elise van der Pol; Thomas Kipf; Frans A. Oliehoek; Max Welling (AAMAS, 2020)

Maximizing Information Gain in Partially Observable Environments via Prediction Rewards. - Yash Satsangi; Sungsu Lim; Shimon Whiteson; Frans A. Oliehoek; Martha White (AAMAS, 2020)

Decentralized MCTS via Learned Teammate Models. - Aleksander Czechowski; Frans A. Oliehoek (IJCAI, 2020)

Sensor Data for Human Activity Recognition: Feature Representation and Benchmarking. - Flávia Alves; Martin Gairing; Frans A. Oliehoek; Thanh-Toan Do (IJCNN, 2020)

Influence-Augmented Online Planning for Complex Environments. - Jinke He; Miguel Suau; Frans A. Oliehoek (NeurIPS, 2020)

Multi-agent active perception with prediction rewards. - Mikko Lauri; Frans A. Oliehoek (NeurIPS, 2020)

MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning. - Elise van der Pol; Daniel E. Worrall; Herke van Hoof; Frans A. Oliehoek; Max Welling (NeurIPS, 2020)

A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence. - 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; et al. (Computer, 2020)

Mimicking Evolution with Reinforcement Learning. - João P. Abrantes; Arnaldo J. Abrantes; Frans A. Oliehoek (CoRR, 2020)

Diversity in Action: General-Sum Multi-Agent Continuous Inverse Optimal Control. - Christian Muench; Frans A. Oliehoek; Dariu M. Gavrila (CoRR, 2020)

Maximizing Information Gain in Partially Observable Environments via Prediction Reward. - Yash Satsangi; Sungsu Lim; Shimon Whiteson; Frans A. Oliehoek; Martha White (CoRR, 2020)

Analog Circuit Design with Dyna-Style Reinforcement Learning. - Wook Lee; Frans A. Oliehoek (CoRR, 2020)

Abstraction-Guided Policy Recovery from Expert Demonstrations. - Canmanie T. Ponnambalam; Frans A. Oliehoek; Matthijs T. J. Spaan (ICAPS, 2021)

Loss Bounds for Approximate Influence-Based Abstraction. - Elena Congeduti; Alexander Mey; Frans A. Oliehoek (AAMAS, 2021)

Environment Shift Games: Are Multiple Agents the Solution, and not the Problem, to Non-Stationarity? - Alexander Mey; Frans A. Oliehoek (AAMAS, 2021)

Learning Complex Policy Distribution with CEM Guided Adversarial Hypernetwork. - Shi Yuan Tang; Athirai A. Irissappane; Frans A. Oliehoek; Jie Zhang 002 (AAMAS, 2021)

ReproducedPapers.org: Openly Teaching and Structuring Machine Learning Reproducibility. - 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 (RRPR, 2021)

Analysing factorizations of action-value networks for cooperative multi-agent reinforcement learning. - Jacopo Castellini; Frans A. Oliehoek; Rahul Savani; Shimon Whiteson (Auton. Agents Multi Agent Syst., 2021)

A Sufficient Statistic for Influence in Structured Multiagent Environments. - Frans A. Oliehoek; Stefan J. Witwicki; Leslie Pack Kaelbling (J. Artif. Intell. Res., 2021)

General-Sum Multi-Agent Continuous Inverse Optimal Control. - Christian Neumeyer; Frans A. Oliehoek; Dariu M. Gavrila (IEEE Robotics Autom. Lett., 2021)

Best-Response Bayesian Reinforcement Learning with Bayes-adaptive POMDPs for Centaurs. - Mustafa Mert Çelikok; Frans A. Oliehoek; Samuel Kaski (AAMAS, 2022)

BADDr: Bayes-Adaptive Deep Dropout RL for POMDPs. - Sammie Katt; Hai Nguyen 001; Frans A. Oliehoek; Christopher Amato (AAMAS, 2022)

MORAL: Aligning AI with Human Norms through Multi-Objective Reinforced Active Learning. - Markus Peschl; Arkady Zgonnikov; Frans A. Oliehoek; Luciano Cavalcante Siebert (AAMAS, 2022)

Speeding up Deep Reinforcement Learning through Influence-Augmented Local Simulators. - Miguel Suau; Jinke He; Matthijs T. J. Spaan; Frans A. Oliehoek (AAMAS, 2022)

Model-Based Reinforcement Learning with State Abstraction: A Survey. - Rolf A. N. Starre; Marco Loog; Frans A. Oliehoek (BNAIC/BENELEARN, 2022)

Multi Robot Surveillance and Planning in Limited Communication Environments. - Vibhav Inna Kedege; Aleksander Czechowski; Ludo Stellingwerff; Frans A. Oliehoek (ICAART (1), 2022)

Multi-Agent MDP Homomorphic Networks. - Elise van der Pol; Herke van Hoof; Frans A. Oliehoek; Max Welling (ICLR, 2022)

On the Impossibility of Learning to Cooperate with Adaptive Partner Strategies in Repeated Games. - Robert Tyler Loftin; Frans A. Oliehoek (ICML, 2022)

Influence-Augmented Local Simulators: a Scalable Solution for Fast Deep RL in Large Networked Systems. - Miguel Suau; Jinke He; Matthijs T. J. Spaan; Frans A. Oliehoek (ICML, 2022)

Online Planning in POMDPs with Self-Improving Simulators. - Jinke He; Miguel Suau; Hendrik Baier; Michael Kaisers; Frans A. Oliehoek (IJCAI, 2022)

Distributed Influence-Augmented Local Simulators for Parallel MARL in Large Networked Systems. - Miguel Suau; Jinke He; Mustafa Mert Çelikok; Matthijs T. J. Spaan; Frans A. Oliehoek (NeurIPS, 2022)

An Analysis of Abstracted Model-Based Reinforcement Learning. - Rolf A. N. Starre; Marco Loog; Frans A. Oliehoek (CoRR, 2022)

Safety Guarantees in Multi-agent Learning via Trapping Regions. - Aleksander Czechowski; Frans A. Oliehoek (AAMAS, 2023)

Safe Multi-agent Learning via Trapping Regions. - Aleksander Czechowski; Frans A. Oliehoek (IJCAI, 2023)

What Lies beyond the Pareto Front? A Survey on Decision-Support Methods for Multi-Objective Optimization. - Zuzanna Osika; Jazmin Zatarain Salazar; Diederik M. Roijers; Frans A. Oliehoek; Pradeep K. Murukannaiah (IJCAI, 2023)

Towards a Unifying Model of Rationality in Multiagent Systems. - Robert Tyler Loftin; Mustafa Mert Çelikok; Frans A. Oliehoek (CoRR, 2023)

What model does MuZero learn? - Jinke He; Thomas M. Moerland; Frans A. Oliehoek (CoRR, 2023)

An Analysis of Model-Based Reinforcement Learning From Abstracted Observations. - Rolf A. N. Starre; Marco Loog; Elena Congeduti; Frans A. Oliehoek (Trans. Mach. Learn. Res., 2023)

Teacher-apprentices RL (TARL): leveraging complex policy distribution through generative adversarial hypernetwork in reinforcement learning. - Shi Yuan Tang; Athirai A. Irissappane; Frans A. Oliehoek; Jie Zhang 002 (Auton. Agents Multi Agent Syst., 2023)

Explaining Learned Reward Functions with Counterfactual Trajectories. - Jan Wehner; Frans A. Oliehoek; Luciano Cavalcante Siebert (AIEB@ECAI, 2024)

Uncoupled Learning of Differential Stackelberg Equilibria with Commitments. - Robert T. Loftin; Mustafa Mert Çelikok; Herke van Hoof; Samuel Kaski; Frans A. Oliehoek (AAMAS, 2024)

What Model Does MuZero Learn? - Jinke He; Thomas M. Moerland; Joery A. de Vries; Frans A. Oliehoek (ECAI, 2024)

Navigating Trade-offs: Policy Summarization for Multi-Objective Reinforcement Learning. - Zuzanna Osika; Jazmin Zatarain Salazar; Frans A. Oliehoek; Pradeep K. Murukannaiah (ECAI, 2024)

Communicating with Speakers and Listeners of Different Pragmatic Levels. - Kata Naszádi; Frans A. Oliehoek; Christof Monz (EMNLP, 2024)

Policy Space Response Oracles: A Survey. - Ariyan Bighashdel; Yongzhao Wang 001; Stephen McAleer; Rahul Savani; Frans A. Oliehoek (IJCAI, 2024)

Online Planning in POMDPs with State-Requests. - Raphaël Avalos; Eugenio Bargiacchi; Ann Nowé; Diederik M. Roijers; Frans A. Oliehoek (RLJ, 2024)

Bad Habits: Policy Confounding and Out-of-Trajectory Generalization in RL. - Miguel Suau; Matthijs T. J. Spaan; Frans A. Oliehoek (RLJ, 2024)

When Do Off-Policy and On-Policy Policy Gradient Methods Align? - Davide Mambelli; Stephan Bongers; Onno Zoeter; Matthijs T. J. Spaan; Frans A. Oliehoek (CoRR, 2024)

Inverse Concave-Utility Reinforcement Learning is Inverse Game Theory. - Mustafa Mert Çelikok; Frans A. Oliehoek; Jan-Willem van de Meent (CoRR, 2024)

Task-unaware Lifelong Robot Learning with Retrieval-based Weighted Local Adaptation. - Pengzhi Yang; Xinyu Wang; Ruipeng Zhang; Cong Wang; Frans A. Oliehoek; Jens Kober (CoRR, 2024)

SimuDICE: Offline Policy Optimization Through World Model Updates and DICE Estimation. - Catalin E. Brita; Stephan Bongers; Frans A. Oliehoek (CoRR, 2024)

A Survey on Scenario Theory, Complexity, and Compression-Based Learning and Generalization. - Roberto Rocchetta; Alexander Mey; Frans A. Oliehoek (IEEE Trans. Neural Networks Learn. Syst., 2024)

Multi-Objective Reinforcement Learning for Water Management. - Zuzanna Osika; Roxana Radulescu; Jazmin Zatarain Salazar; Frans A. Oliehoek; Pradeep K. Murukannaiah (AAMAS, 2025)

Influence Learning in Complex Systems. - Elena Congeduti; Roberto Rocchetta; Frans A. Oliehoek (Trans. Mach. Learn. Res., 2025)

Abstraction for Bayesian Reinforcement Learning in Factored POMDPs. - Rolf A. N. Starre; Sammie Katt; Mustafa Mert Çelikok; Marco Loog; Frans A. Oliehoek (Trans. Mach. Learn. Res., 2025)

SHARPIE: A Modular Framework for Reinforcement Learning and Human-AI Interaction Experiments. - Hüseyin Aydin; Kevin Godin-Dubois; Libio Goncalvez Braz; Floris den Hengst; Kim Baraka; Mustafa Mert Çelikok; Andreas Sauter; Shihan Wang 001; Frans A. Oliehoek (CoRR, 2025)

Timing the Match: A Deep Reinforcement Learning Approach for Ride-Hailing and Ride-Pooling Services. - Yiman Bao; Jie Gao 010; Jinke He; Frans A. Oliehoek; Oded Cats (CoRR, 2025)

Exploring Equity of Climate Policies using Multi-Agent Multi-Objective Reinforcement Learning. - Palok Biswas; Zuzanna Osika; Isidoro Tamassia; Adit Whorra; Jazmin Zatarain Salazar; Jan H. Kwakkel; Frans A. Oliehoek; Pradeep K. Murukannaiah (CoRR, 2025)

Difference rewards policy gradients. - Jacopo Castellini; Sam Devlin; Frans A. Oliehoek; Rahul Savani (Neural Comput. Appl., 2025)

Influence-aware memory architectures for deep reinforcement learning in POMDPs. - Miguel Suau; Jinke He; Elena Congeduti; Rolf A. N. Starre; Aleksander Czechowski; Frans A. Oliehoek (Neural Comput. Appl., 2025)