Probability estimation and a competence model for rule based e-tutoring systems. - Diederik M. Roijers; Johan Jeuring; Ad Feelders (LAK, 2012)

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

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

A Survey of Multi-Objective Sequential Decision-Making. - Diederik M. Roijers; Peter Vamplew 001; Shimon Whiteson; Richard Dazeley (J. Artif. Intell. Res., 2013)

Towards Personalised Gaming via Facial Expression Recognition. - Paris Mavromoustakos Blom; Sander Bakkes; Chek Tien Tan; Shimon Whiteson; Diederik M. Roijers; Roberto Valenti; Theo Gevers (AIIDE, 2014)

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)

Convex coverage set methods for multi-objective collaborative decision making. - Diederik M. Roijers (AAMAS, 2014)

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

Circuit-adaptive challenge balancing in racing games. - Alex Rietveld; Sander Bakkes; Diederik M. Roijers (GEM, 2014)

Queued Pareto Local Search for Multi-Objective Optimization. - Maarten Inja; Chiel Kooijman; Maarten de Waard; Diederik M. Roijers; Shimon Whiteson (PPSN, 2014)

Pareto Local Search for MOMDP Planning. - Chiel Kooijman; Maarten de Waard; Maarten Inja; Diederik M. Roijers; Shimon Whiteson (ESANN, 2015)

Grammar-based Procedural Content Generation from Designer-provided Difficulty Curves. - Mircea Traichioiu; Sander Bakkes; Diederik M. Roijers (FDG, 2015)

Efficient Methods for Multi-Objective Decision-Theoretic Planning. - Diederik Marijn Roijers (IJCAI, 2015)

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

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)

Monte Carlo Tree Search with options for general video game playing. - Maarten de Waard; Diederik M. Roijers; Sander C. J. Bakkes (CIG, 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)

Balancing Relevance Criteria through Multi-Objective Optimization. - Joost van Doorn; Daan Odijk; Diederik M. Roijers; Maarten de Rijke (SIGIR, 2016)

Multi-objective decision-theoretic planning: abstract. - Diederik M. Roijers (AI Matters, 2016)

Multi-Objective Deep Reinforcement Learning. - Hossam Mossalam; Yannis M. Assael; Diederik M. Roijers; Shimon Whiteson (CoRR, 2016)

Multi-criteria Coalition Formation Games. - Ayumi Igarashi 001; Diederik M. Roijers (ADT, 2017)

Interactive Thompson Sampling for Multi-objective Multi-armed Bandits. - Diederik M. Roijers; Luisa M. Zintgraf; Ann Nowé (ADT, 2017)

Efficient Evaluation of Influenza Mitigation Strategies Using Preventive Bandits. - Pieter Libin; Timothy Verstraeten; Kristof Theys; Diederik M. Roijers; Peter Vrancx; Ann Nowé (AAMAS Workshops (Visionary Papers), 2017)

Reinforcement Learning in POMDPs with Memoryless Options and Option-Observation Initiation Sets. - Denis Steckelmacher; Diederik M. Roijers; Anna Harutyunyan; Peter Vrancx; Ann Nowé (CoRR, 2017)

Multi-Objective Decision Making - Diederik M. Roijers; Shimon Whiteson (Morgan & Claypool Publishers, 2017)

Reinforcement Learning in POMDPs With Memoryless Options and Option-Observation Initiation Sets. - Denis Steckelmacher; Diederik M. Roijers; Anna Harutyunyan; Peter Vrancx; Hélène Plisnier; Ann Nowé (AAAI, 2018)

Bootstrapping LPs in Value Iteration for Multi-Objective and Partially Observable MDPs. - Diederik M. Roijers; Erwin Walraven; Matthijs T. J. Spaan (ICAPS, 2018)

Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making. - Luisa M. Zintgraf; Diederik M. Roijers; Sjoerd Linders; Catholijn M. Jonker; Ann Nowé (AAMAS, 2018)

Deep Multi-agent Reinforcement Learning in a Homogeneous Open Population. - Roxana Radulescu; Manon Legrand; Kyriakos Efthymiadis; Diederik M. Roijers; Ann Nowé (BNCAI, 2018)

Real-Time Robot Vision on Low-Performance Computing Hardware. - Gongjin Lan; Jesús Benito-Picazo; Diederik M. Roijers; Enrique Domínguez; A. E. Eiben (ICARCV, 2018)

Predicting Appliance Usage Status In Home Like Environments. - Jie Jiang 011; Mark Hoogendoorn; Qiuqiang Kong; Diederik M. Roijers; Nigel Gilbert (DSP, 2018)

Learning to Coordinate with Coordination Graphs in Repeated Single-Stage Multi-Agent Decision Problems. - Eugenio Bargiacchi; Timothy Verstraeten; Diederik M. Roijers; Ann Nowé; Hado van Hasselt (ICML, 2018)

Analysing the Relative Importance of Robot Brains and Bodies. - Milan Jelisavcic; Diederik M. Roijers; A. E. Eiben (ALIFE, 2018)

Bayesian Best-Arm Identification for Selecting Influenza Mitigation Strategies. - Pieter J. K. Libin; Timothy Verstraeten; Diederik M. Roijers; Jelena Grujic; Kristof Theys; Philippe Lemey; Ann Nowé (ECML/PKDD (3), 2018)

Directed Locomotion for Modular Robots with Evolvable Morphologies. - Gongjin Lan; Milan Jelisavcic; Diederik M. Roijers; Evert Haasdijk; A. E. Eiben (PPSN (1), 2018)

Directed Policy Gradient for Safe Reinforcement Learning with Human Advice. - Hélène Plisnier; Denis Steckelmacher; Tim Brys; Diederik M. Roijers; Ann Nowé (CoRR, 2018)

Open-Ended Learning: A Conceptual Framework Based on Representational Redescription. - Stéphane Doncieux; David Filliat; Natalia Díaz Rodríguez; Timothy M. Hospedales; Richard J. Duro; Alexandre Coninx; Diederik M. Roijers; Benoît Girard 001; Nicolas Perrin 001; Olivier Sigaud (Frontiers Neurorobotics, 2018)

A Scalable Logo Recognition Model with Deep Meta-Learning. - Mark de Blaauw; Diederik M. Roijers; Vesa Muhonen (BNAIC/BENELEARN, 2019)

Thompson Sampling for m-top Exploration. - Pieter Libin; Timothy Verstraeten; Diederik M. Roijers; Wenjia Wang; Kristof Theys; Ann Nowé (BNAIC/BENELEARN, 2019)

Transfer Reinforcement Learning across Environment Dynamics with Multiple Advisors. - Hélène Plisnier; Denis Steckelmacher; Diederik M. Roijers; Ann Nowé (BNAIC/BENELEARN, 2019)

Dynamic Weights in Multi-Objective Deep Reinforcement Learning. - Axel Abels; Diederik M. Roijers; Tom Lenaerts; Ann Nowé; Denis Steckelmacher (ICML, 2019)

Bayesian Anytime m-top Exploration. - Pieter Libin; Timothy Verstraeten; Diederik M. Roijers; Wenjia Wang; Kristof Theys; Ann Nowé (ICTAI, 2019)

Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics. - Denis Steckelmacher; Hélène Plisnier; Diederik M. Roijers; Ann Nowé (ECML/PKDD (3), 2019)

The Actor-Advisor: Policy Gradient With Off-Policy Advice. - Hélène Plisnier; Denis Steckelmacher; Diederik M. Roijers; Ann Nowé (CoRR, 2019)

Transfer Learning Across Simulated Robots With Different Sensors. - Hélène Plisnier; Denis Steckelmacher; Diederik M. Roijers; Ann Nowé (CoRR, 2019)

DCRAC: Deep Conditioned Recurrent Actor-Critic for Multi-Objective Partially Observable Environments. - Xiaodong Nian; Athirai Aravazhi Irissappane; Diederik M. Roijers (AAMAS, 2020)

Thompson Sampling for Factored Multi-Agent Bandits. - Timothy Verstraeten; Eugenio Bargiacchi; Pieter J. K. Libin; Diederik M. Roijers; Ann Nowé (AAMAS, 2020)

Opponent Modelling for Reinforcement Learning in Multi-Objective Normal Form Games. - Yijie Zhang; Roxana Radulescu; Patrick Mannion; Diederik M. Roijers; Ann Nowé (AAMAS, 2020)

Deep Reinforcement Learning for Solving Train Unit Shunting Problem with Interval Timing. - Wan-Jui Lee; Helia Jamshidi; Diederik M. Roijers (EDCC Workshops, 2020)

Interactive Multi-objective Reinforcement Learning in Multi-armed Bandits with Gaussian Process Utility Models. - Diederik M. Roijers; Luisa M. Zintgraf; Pieter Libin; Mathieu Reymond; Eugenio Bargiacchi; Ann Nowé (ECML/PKDD (3), 2020)

Multi-objective multi-agent decision making: a utility-based analysis and survey. - Roxana Radulescu; Patrick Mannion; Diederik M. Roijers; Ann Nowé (Auton. Agents Multi Agent Syst., 2020)

Model-based Multi-Agent Reinforcement Learning with Cooperative Prioritized Sweeping. - Eugenio Bargiacchi; Timothy Verstraeten; Diederik M. Roijers; Ann Nowé (CoRR, 2020)

AI-Toolbox: A C++ library for Reinforcement Learning and Planning (with Python Bindings). - Eugenio Bargiacchi; Diederik M. Roijers; Ann Nowé (J. Mach. Learn. Res., 2020)

A utility-based analysis of equilibria in multi-objective normal-form games. - Roxana Radulescu; Patrick Mannion; Yijie Zhang; Diederik M. Roijers; Ann Nowé (Knowl. Eng. Rev., 2020)

Avatars of a Feather Flock Together: Gender Homophily in Online Video Games Revealed via Exponential Random Graph Modeling. - Shiyu Zhang; Sander Bakkes; Diederik M. Roijers; Pieter Spronck (IEEE Trans. Games, 2020)

Coordination of Electric Vehicle Charging Through Multiagent Reinforcement Learning. - Felipe Leno da Silva; Cyntia Eico Hayama Nishida; Diederik M. Roijers; Anna Helena Reali Costa (IEEE Trans. Smart Grid, 2020)

Cooperative Prioritized Sweeping. - Eugenio Bargiacchi; Timothy Verstraeten; Diederik M. Roijers (AAMAS, 2021)

Distributional Monte Carlo Tree Search for Risk-Aware and Multi-Objective Reinforcement Learning. - Conor F. Hayes; Mathieu Reymond; Diederik M. Roijers; Enda Howley; Patrick Mannion (AAMAS, 2021)

Scalable Optimization for Wind Farm Control using Coordination Graphs. - Timothy Verstraeten; Pieter-Jan Daems; Eugenio Bargiacchi; Diederik M. Roijers; Pieter J. K. Libin; Jan Helsen (AAMAS, 2021)

Learning directed locomotion in modular robots with evolvable morphologies. - Gongjin Lan; Matteo De Carlo; Fuda van Diggelen; Jakub M. Tomczak; Diederik M. Roijers; A. E. Eiben (Appl. Soft Comput., 2021)

Risk Aware and Multi-Objective Decision Making with Distributional Monte Carlo Tree Search. - Conor F. Hayes; Mathieu Reymond; Diederik M. Roijers; Enda Howley; Patrick Mannion (CoRR, 2021)

Deep Learning-Based Energy Disaggregation and On/Off Detection of Household Appliances. - Jie Jiang 011; Qiuqiang Kong; Mark D. Plumbley; Nigel Gilbert; Mark Hoogendoorn; Diederik M. Roijers (ACM Trans. Knowl. Discov. Data, 2021)

Local Advantage Networks for Cooperative Multi-Agent Reinforcement Learning. - Raphaël Avalos; Mathieu Reymond; Ann Nowé; Diederik M. Roijers (AAMAS, 2022)

Decision-Theoretic Planning for the Expected Scalarised Returns. - Conor F. Hayes; Diederik M. Roijers; Enda Howley; Patrick Mannion (AAMAS, 2022)

Near On-Policy Experience Sampling in Multi-Objective Reinforcement Learning. - Shang Wang; Mathieu Reymond; Athirai A. Irissappane; Diederik M. Roijers (AAMAS, 2022)

A practical guide to multi-objective reinforcement learning and planning. - Conor F. Hayes; Roxana Radulescu; Eugenio Bargiacchi; Johan Källström; Matthew Macfarlane; Mathieu Reymond; Timothy Verstraeten; Luisa M. Zintgraf; Richard Dazeley; Fredrik Heintz; Enda Howley; Athirai A. Irissappane; et al. (Auton. Agents Multi Agent Syst., 2022)

On nash equilibria in normal-form games with vectorial payoffs. - Willem Röpke; Diederik M. Roijers; Ann Nowé; Roxana Radulescu (Auton. Agents Multi Agent Syst., 2022)

Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021). - Peter Vamplew 001; Benjamin J. Smith; Johan Källström; Gabriel de Oliveira Ramos; Roxana Radulescu; Diederik M. Roijers; Conor F. Hayes; Fredrik Heintz; Patrick Mannion; Pieter J. K. Libin; Richard Dazeley; Cameron Foale (Auton. Agents Multi Agent Syst., 2022)

Multi-Objective Coordination Graphs for the Expected Scalarised Returns with Generative Flow Models. - Conor F. Hayes; Timothy Verstraeten; Diederik M. Roijers; Enda Howley; Patrick Mannion (CoRR, 2022)

Determining Accessible Sidewalk Width by Extracting Obstacle Information from Point Clouds. - Cláudia Fonseca Pinhão; Chris Eijgenstein; Iva Gornishka; Shayla Jansen; Diederik M. Roijers; Daan Bloembergen (CoRR, 2022)

Opponent learning awareness and modelling in multi-objective normal form games. - Roxana Radulescu; Timothy Verstraeten; Yijie Zhang; Patrick Mannion; Diederik M. Roijers; Ann Nowé (Neural Comput. Appl., 2022)

Time efficiency in optimization with a bayesian-Evolutionary algorithm. - Gongjin Lan; Jakub M. Tomczak; Diederik M. Roijers; A. E. Eiben (Swarm Evol. Comput., 2022)

Scalar Reward is Not Enough. - Peter Vamplew 001; Benjamin J. Smith; Johan Källström; Gabriel de Oliveira Ramos; Roxana Radulescu; Diederik M. Roijers; Conor F. Hayes; Friedrik Hentz; Patrick Mannion; Pieter J. K. Libin; Richard Dazeley; Cameron Foale (AAMAS, 2023)

Sample-Efficient Multi-Objective Learning via Generalized Policy Improvement Prioritization. - Lucas Nunes Alegre; Ana L. C. Bazzan; Diederik M. Roijers; Ann Nowé; Bruno C. da Silva 001 (AAMAS, 2023)

A Brief Guide to Multi-Objective Reinforcement Learning and Planning. - Conor F. Hayes; Roxana Radulescu; Eugenio Bargiacchi; Johan Källström; Matthew Macfarlane; Mathieu Reymond; Timothy Verstraeten; Luisa M. Zintgraf; Richard Dazeley; Fredrik Heintz; Enda Howley; Athirai A. Irissappane; et al. (AAMAS, 2023)

Bridging the Gap Between Single and Multi Objective Games. - Willem Röpke; Carla Groenland; Roxana Radulescu; Ann Nowé; Diederik M. Roijers (AAMAS, 2023)

A Study of Nash Equilibria in Multi-Objective Normal-Form Games. - Willem Röpke; Diederik M. Roijers; Ann Nowé; Roxana Radulescu (AAMAS, 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)

Distributional Multi-Objective Decision Making. - Willem Röpke; Conor F. Hayes; Patrick Mannion; Enda Howley; Ann Nowé; Diederik M. Roijers (IJCAI, 2023)

Local Advantage Networks for Multi-Agent Reinforcement Learning in Dec-POMDPs. - Raphaël Avalos; Mathieu Reymond; Ann Nowé; Diederik M. Roijers (Trans. Mach. Learn. Res., 2023)

Monte Carlo tree search algorithms for risk-aware and multi-objective reinforcement learning. - Conor F. Hayes; Mathieu Reymond; Diederik M. Roijers; Enda Howley; Patrick Mannion (Auton. Agents Multi Agent Syst., 2023)

Actor-critic multi-objective reinforcement learning for non-linear utility functions. - Mathieu Reymond; Conor F. Hayes; Denis Steckelmacher; Diederik M. Roijers; Ann Nowé (Auton. Agents Multi Agent Syst., 2023)

Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning. - Peter Vamplew 001; Cameron Foale; Conor F. Hayes; Patrick Mannion; Enda Howley; Richard Dazeley; Scott Johnson; Johan Källström; Gabriel de Oliveira Ramos; Roxana Radulescu; Willem Röpke; Diederik M. Roijers (AAMAS, 2024)

Interactively Learning the User's Utility for Best-Arm Identification in Multi-Objective Multi-Armed Bandits. - Mathieu Reymond; Eugenio Bargiacchi; Diederik M. Roijers; Ann Nowé (AAMAS, 2024)

The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models. - Raphaël Avalos; Florent Delgrange; Ann Nowé; Guillermo A. Pérez 001; Diederik M. Roijers (ICLR, 2024)

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

Deep Multi-Objective Reinforcement Learning for Utility-Based Infrastructural Maintenance Optimization. - Jesse van Remmerden; Maurice Kenter; Diederik M. Roijers; Charalampos Andriotis; Yingqian Zhang 001; Zaharah Bukhsh (CoRR, 2024)

MOMAland: A Set of Benchmarks for Multi-Objective Multi-Agent Reinforcement Learning. - Florian Felten; Umut Ucak; Hicham Azmani; Gao Peng; Willem Röpke; Hendrik Baier; Patrick Mannion; Diederik M. Roijers; Jordan K. Terry; El-Ghazali Talbi; Grégoire Danoy; Ann Nowé; et al. (CoRR, 2024)

Scalable Multi-Objective Reinforcement Learning with Fairness Guarantees using Lorenz Dominance. - Dimitris Michailidis; Willem Röpke; Diederik M. Roijers; Sennay Ghebreab; Fernando P. Santos (CoRR, 2024)

Exploring the Pareto front of multi-objective COVID-19 mitigation policies using reinforcement learning. - Mathieu Reymond; Conor F. Hayes; Lander Willem; Roxana Radulescu; Steven Abrams; Diederik M. Roijers; Enda Howley; Patrick Mannion; Niel Hens; Ann Nowé; Pieter Libin (Expert Syst. Appl., 2024)

Divide and Conquer: Provably Unveiling the Pareto Front with Multi-Objective Reinforcement Learning. - Willem Röpke; Mathieu Reymond; Patrick Mannion; Diederik M. Roijers; Ann Nowé; Roxana Radulescu (AAMAS, 2025)

Expected scalarised returns dominance: a new solution concept for multi-objective decision making. - Conor F. Hayes; Timothy Verstraeten; Diederik M. Roijers; Enda Howley; Patrick Mannion (Neural Comput. Appl., 2025)

Preference communication in multi-objective normal-form games. - Willem Röpke; Diederik M. Roijers; Ann Nowé; Roxana Radulescu (Neural Comput. Appl., 2025)