Diederik M. Roijers

ORCID

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 103

Top Venues

CoRR

AAMAS

Auton. Agents Multi Agent Syst.

BNAIC/BENELEARN

Publications

Mathieu Reymond, Eugenio Bargiacchi, Diederik M. Roijers, Ann Nowé
Interactively Learning the User's Utility for Best-Arm Identification in Multi-Objective Multi-Armed Bandits. AAMAS (2024)
Raphaël Avalos, Florent Delgrange, Ann Nowé, Guillermo A. Pérez, Diederik M. Roijers
The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models. ICLR (2024)
Peter Vamplew, 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
Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning. CoRR (2024)
Jesse van Remmerden, Maurice Kenter, Diederik M. Roijers, Charalampos Andriotis, Yingqian Zhang, Zaharah Bukhsh
Deep Multi-Objective Reinforcement Learning for Utility-Based Infrastructural Maintenance Optimization. CoRR (2024)
Peter Vamplew, 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
Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning. AAMAS (2024)
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, Roxana Radulescu
MOMAland: A Set of Benchmarks for Multi-Objective Multi-Agent Reinforcement Learning. CoRR (2024)
Mathieu Reymond, Conor F. Hayes, Lander Willem, Roxana Radulescu, Steven Abrams, Diederik M. Roijers, Enda Howley, Patrick Mannion, Niel Hens, Ann Nowé, Pieter Libin
Exploring the Pareto front of multi-objective COVID-19 mitigation policies using reinforcement learning. Expert Syst. Appl. 249 (2024)
Raphaël Avalos, Eugenio Bargiacchi, Ann Nowé, Diederik M. Roijers, Frans A. Oliehoek
Online Planning in POMDPs with State-Requests. CoRR (2024)
Willem Röpke, Mathieu Reymond, Patrick Mannion, Diederik M. Roijers, Ann Nowé, Roxana Radulescu
Divide and Conquer: Provably Unveiling the Pareto Front with Multi-Objective Reinforcement Learning. CoRR (2024)
Willem Röpke, Conor F. Hayes, Patrick Mannion, Enda Howley, Ann Nowé, Diederik M. Roijers
Distributional Multi-Objective Decision Making. IJCAI (2023)
Mathieu Reymond, Conor F. Hayes, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé
Actor-critic multi-objective reinforcement learning for non-linear utility functions. Auton. Agents Multi Agent Syst. 37 (2) (2023)
Willem Röpke, Diederik M. Roijers, Ann Nowé, Roxana Radulescu
A Study of Nash Equilibria in Multi-Objective Normal-Form Games. AAMAS (2023)
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, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers
A Brief Guide to Multi-Objective Reinforcement Learning and Planning. AAMAS (2023)
Willem Röpke, Conor F. Hayes, Patrick Mannion, Enda Howley, Ann Nowé, Diederik M. Roijers
Distributional Multi-Objective Decision Making. CoRR (2023)
Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley, Patrick Mannion
Monte Carlo tree search algorithms for risk-aware and multi-objective reinforcement learning. Auton. Agents Multi Agent Syst. 37 (2) (2023)
Lucas Nunes Alegre, Ana L. C. Bazzan, Diederik M. Roijers, Ann Nowé, Bruno C. da Silva
Sample-Efficient Multi-Objective Learning via Generalized Policy Improvement Prioritization. CoRR (2023)
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 (2023)
Willem Röpke, Carla Groenland, Roxana Radulescu, Ann Nowé, Diederik M. Roijers
Bridging the Gap Between Single and Multi Objective Games. CoRR (2023)
Raphaël Avalos, Florent Delgrange, Ann Nowé, Guillermo A. Pérez, Diederik M. Roijers
The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models. CoRR (2023)
Willem Röpke, Carla Groenland, Roxana Radulescu, Ann Nowé, Diederik M. Roijers
Bridging the Gap Between Single and Multi Objective Games. AAMAS (2023)
Raphaël Avalos, Mathieu Reymond, Ann Nowé, Diederik M. Roijers
Local Advantage Networks for Multi-Agent Reinforcement Learning in Dec-POMDPs. Trans. Mach. Learn. Res. 2023 (2023)
Lucas Nunes Alegre, Ana L. C. Bazzan, Diederik M. Roijers, Ann Nowé, Bruno C. da Silva
Sample-Efficient Multi-Objective Learning via Generalized Policy Improvement Prioritization. AAMAS (2023)
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)
Peter Vamplew, 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
Scalar Reward is Not Enough. AAMAS (2023)
Gongjin Lan, Jakub M. Tomczak, Diederik M. Roijers, A. E. Eiben
Time efficiency in optimization with a bayesian-Evolutionary algorithm. Swarm Evol. Comput. 69 (2022)
Conor F. Hayes, Diederik M. Roijers, Enda Howley, Patrick Mannion
Decision-Theoretic Planning for the Expected Scalarised Returns. AAMAS (2022)
Raphaël Avalos, Mathieu Reymond, Ann Nowé, Diederik M. Roijers
Local Advantage Networks for Cooperative Multi-Agent Reinforcement Learning. AAMAS (2022)
Roxana Radulescu, Timothy Verstraeten, Yijie Zhang, Patrick Mannion, Diederik M. Roijers, Ann Nowé
Opponent learning awareness and modelling in multi-objective normal form games. Neural Comput. Appl. 34 (3) (2022)
Cláudia Fonseca Pinhão, Chris Eijgenstein, Iva Gornishka, Shayla Jansen, Diederik M. Roijers, Daan Bloembergen
Determining Accessible Sidewalk Width by Extracting Obstacle Information from Point Clouds. CoRR (2022)
Peter Vamplew, 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
Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021). Auton. Agents Multi Agent Syst. 36 (2) (2022)
Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley, Patrick Mannion
Monte Carlo Tree Search Algorithms for Risk-Aware and Multi-Objective Reinforcement Learning. CoRR (2022)
Willem Röpke, Diederik M. Roijers, Ann Nowé, Roxana Radulescu
On nash equilibria in normal-form games with vectorial payoffs. Auton. Agents Multi Agent Syst. 36 (2) (2022)
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, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers
A practical guide to multi-objective reinforcement learning and planning. Auton. Agents Multi Agent Syst. 36 (1) (2022)
Mathieu Reymond, Conor F. Hayes, Lander Willem, Roxana Radulescu, Steven Abrams, Diederik M. Roijers, Enda Howley, Patrick Mannion, Niel Hens, Ann Nowé, Pieter Libin
Exploring the Pareto front of multi-objective COVID-19 mitigation policies using reinforcement learning. CoRR (2022)
Conor F. Hayes, Timothy Verstraeten, Diederik M. Roijers, Enda Howley, Patrick Mannion
Multi-Objective Coordination Graphs for the Expected Scalarised Returns with Generative Flow Models. CoRR (2022)
Shang Wang, Mathieu Reymond, Athirai A. Irissappane, Diederik M. Roijers
Near On-Policy Experience Sampling in Multi-Objective Reinforcement Learning. AAMAS (2022)
Willem Röpke, Diederik M. Roijers, Ann Nowé, Roxana Radulescu
Preference Communication in Multi-Objective Normal-Form Games. CoRR (2021)
Timothy Verstraeten, Pieter-Jan Daems, Eugenio Bargiacchi, Diederik M. Roijers, Pieter J. K. Libin, Jan Helsen
Scalable Optimization for Wind Farm Control using Coordination Graphs. CoRR (2021)
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, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers
A Practical Guide to Multi-Objective Reinforcement Learning and Planning. CoRR (2021)
Timothy Verstraeten, Pieter-Jan Daems, Eugenio Bargiacchi, Diederik M. Roijers, Pieter J. K. Libin, Jan Helsen
Scalable Optimization for Wind Farm Control using Coordination Graphs. AAMAS (2021)
Peter Vamplew, 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
Scalar reward is not enough: A response to Silver, Singh, Precup and Sutton (2021). CoRR (2021)
Eugenio Bargiacchi, Timothy Verstraeten, Diederik M. Roijers
Cooperative Prioritized Sweeping. AAMAS (2021)
Raphaël Avalos, Mathieu Reymond, Ann Nowé, Diederik M. Roijers
Local Advantage Networks for Cooperative Multi-Agent Reinforcement Learning. CoRR (2021)
Conor F. Hayes, Timothy Verstraeten, Diederik M. Roijers, Enda Howley, Patrick Mannion
Expected Scalarised Returns Dominance: A New Solution Concept for Multi-Objective Decision Making. CoRR (2021)
Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley, Patrick Mannion
Distributional Monte Carlo Tree Search for Risk-Aware and Multi-Objective Reinforcement Learning. AAMAS (2021)
Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley, Patrick Mannion
Risk Aware and Multi-Objective Decision Making with Distributional Monte Carlo Tree Search. CoRR (2021)
Jie Jiang, Qiuqiang Kong, Mark D. Plumbley, Nigel Gilbert, Mark Hoogendoorn, Diederik M. Roijers
Deep Learning-Based Energy Disaggregation and On/Off Detection of Household Appliances. ACM Trans. Knowl. Discov. Data 15 (3) (2021)
Willem Röpke, Diederik M. Roijers, Ann Nowé, Roxana Radulescu
On Nash Equilibria in Normal-Form Games With Vectorial Payoffs. CoRR (2021)
Gongjin Lan, Matteo De Carlo, Fuda van Diggelen, Jakub M. Tomczak, Diederik M. Roijers, A. E. Eiben
Learning directed locomotion in modular robots with evolvable morphologies. Appl. Soft Comput. 111 (2021)
Gongjin Lan, Jakub M. Tomczak, Diederik M. Roijers, A. E. Eiben
Time Efficiency in Optimization with a Bayesian-Evolutionary Algorithm. CoRR (2020)
Felipe Leno da Silva, Cyntia Eico Hayama Nishida, Diederik M. Roijers, Anna Helena Reali Costa
Coordination of Electric Vehicle Charging Through Multiagent Reinforcement Learning. IEEE Trans. Smart Grid 11 (3) (2020)
Roxana Radulescu, Patrick Mannion, Diederik M. Roijers, Ann Nowé
Multi-Objective Multi-Agent Decision Making: A Utility-based Analysis and Survey. AAMAS (2020)
Eugenio Bargiacchi, Diederik M. Roijers, Ann Nowé
AI-Toolbox: A C++ library for Reinforcement Learning and Planning (with Python Bindings). J. Mach. Learn. Res. 21 (2020)
Roxana Radulescu, Timothy Verstraeten, Yijie Zhang, Patrick Mannion, Diederik M. Roijers, Ann Nowé
Opponent Learning Awareness and Modelling in Multi-Objective Normal Form Games. CoRR (2020)
Roxana Radulescu, Patrick Mannion, Yijie Zhang, Diederik M. Roijers, Ann Nowé
A utility-based analysis of equilibria in multi-objective normal form games. CoRR (2020)
Yijie Zhang, Roxana Radulescu, Patrick Mannion, Diederik M. Roijers, Ann Nowé
Opponent Modelling for Reinforcement Learning in Multi-Objective Normal Form Games. AAMAS (2020)
Roxana Radulescu, Patrick Mannion, Diederik M. Roijers, Ann Nowé
Multi-objective multi-agent decision making: a utility-based analysis and survey. Auton. Agents Multi Agent Syst. 34 (1) (2020)
Diederik M. Roijers, Luisa M. Zintgraf, Pieter Libin, Mathieu Reymond, Eugenio Bargiacchi, Ann Nowé
Interactive Multi-objective Reinforcement Learning in Multi-armed Bandits with Gaussian Process Utility Models. ECML/PKDD (3) (2020)
Wan-Jui Lee, Helia Jamshidi, Diederik M. Roijers
Deep Reinforcement Learning for Solving Train Unit Shunting Problem with Interval Timing. EDCC Workshops (2020)
Shiyu Zhang, Sander Bakkes, Diederik M. Roijers, Pieter Spronck
Avatars of a Feather Flock Together: Gender Homophily in Online Video Games Revealed via Exponential Random Graph Modeling. IEEE Trans. Games 12 (1) (2020)
Eugenio Bargiacchi, Timothy Verstraeten, Diederik M. Roijers, Ann Nowé
Model-based Multi-Agent Reinforcement Learning with Cooperative Prioritized Sweeping. CoRR (2020)
Roxana Radulescu, Patrick Mannion, Yijie Zhang, Diederik M. Roijers, Ann Nowé
A utility-based analysis of equilibria in multi-objective normal-form games. Knowl. Eng. Rev. 35 (2020)
Xiaodong Nian, Athirai Aravazhi Irissappane, Diederik M. Roijers
DCRAC: Deep Conditioned Recurrent Actor-Critic for Multi-Objective Partially Observable Environments. AAMAS (2020)
Gongjin Lan, Matteo De Carlo, Fuda van Diggelen, Jakub M. Tomczak, Diederik M. Roijers, A. E. Eiben
Learning Directed Locomotion in Modular Robots with Evolvable Morphologies. CoRR (2020)
Timothy Verstraeten, Eugenio Bargiacchi, Pieter J. K. Libin, Diederik M. Roijers, Ann Nowé
Thompson Sampling for Factored Multi-Agent Bandits. AAMAS (2020)
Timothy Verstraeten, Eugenio Bargiacchi, Pieter J. K. Libin, Diederik M. Roijers, Ann Nowé
Thompson Sampling for Factored Multi-Agent Bandits. CoRR (2019)
Denis Steckelmacher, Hélène Plisnier, Diederik M. Roijers, Ann Nowé
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics. CoRR (2019)
Hélène Plisnier, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé
The Actor-Advisor: Policy Gradient With Off-Policy Advice. CoRR (2019)
Hélène Plisnier, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé
Transfer Learning Across Simulated Robots With Different Sensors. CoRR (2019)
Pieter Libin, Timothy Verstraeten, Diederik M. Roijers, Wenjia Wang, Kristof Theys, Ann Nowé
Thompson Sampling for m-top Exploration. BNAIC/BENELEARN (2019)
Denis Steckelmacher, Hélène Plisnier, Diederik M. Roijers, Ann Nowé
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics. ECML/PKDD (3) (2019)
Pieter Libin, Timothy Verstraeten, Diederik M. Roijers, Wenjia Wang, Kristof Theys, Ann Nowé
Bayesian Anytime m-top Exploration. ICTAI (2019)
Axel Abels, Diederik M. Roijers, Tom Lenaerts, Ann Nowé, Denis Steckelmacher
Dynamic Weights in Multi-Objective Deep Reinforcement Learning. ICML (2019)
Mark de Blaauw, Diederik M. Roijers, Vesa Muhonen
A Scalable Logo Recognition Model with Deep Meta-Learning. BNAIC/BENELEARN (2019)
Roxana Radulescu, Patrick Mannion, Diederik M. Roijers, Ann Nowé
Multi-Objective Multi-Agent Decision Making: A Utility-based Analysis and Survey. CoRR (2019)
Hélène Plisnier, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé
Transfer Reinforcement Learning across Environment Dynamics with Multiple Advisors. BNAIC/BENELEARN (2019)
Denis Steckelmacher, Hélène Plisnier, Diederik M. Roijers, Ann Nowé
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics. BNAIC/BENELEARN (2019)
Denis Steckelmacher, Diederik M. Roijers, Anna Harutyunyan, Peter Vrancx, Hélène Plisnier, Ann Nowé
Reinforcement Learning in POMDPs With Memoryless Options and Option-Observation Initiation Sets. AAAI (2018)
Gongjin Lan, Jesús Benito-Picazo, Diederik M. Roijers, Enrique Domínguez, A. E. Eiben
Real-Time Robot Vision on Low-Performance Computing Hardware. ICARCV (2018)
Stéphane Doncieux, David Filliat, Natalia Díaz Rodríguez, Timothy M. Hospedales, Richard J. Duro, Alexandre Coninx, Diederik M. Roijers, Benoît Girard, Nicolas Perrin, Olivier Sigaud
Open-Ended Learning: A Conceptual Framework Based on Representational Redescription. Frontiers Neurorobotics 12 (2018)
Luisa M. Zintgraf, Diederik M. Roijers, Sjoerd Linders, Catholijn M. Jonker, Ann Nowé
Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making. AAMAS (2018)
Axel Abels, Diederik M. Roijers, Tom Lenaerts, Ann Nowé, Denis Steckelmacher
Dynamic Weights in Multi-Objective Deep Reinforcement Learning. CoRR (2018)
Hélène Plisnier, Denis Steckelmacher, Tim Brys, Diederik M. Roijers, Ann Nowé
Directed Policy Gradient for Safe Reinforcement Learning with Human Advice. CoRR (2018)
Milan Jelisavcic, Diederik M. Roijers, A. E. Eiben
Analysing the Relative Importance of Robot Brains and Bodies. ALIFE (2018)
Pieter J. K. Libin, Timothy Verstraeten, Diederik M. Roijers, Jelena Grujic, Kristof Theys, Philippe Lemey, Ann Nowé
Bayesian Best-Arm Identification for Selecting Influenza Mitigation Strategies. ECML/PKDD (3) (2018)
Eugenio Bargiacchi, Timothy Verstraeten, Diederik M. Roijers, Ann Nowé, Hado van Hasselt
Learning to Coordinate with Coordination Graphs in Repeated Single-Stage Multi-Agent Decision Problems. ICML (2018)
Roxana Radulescu, Manon Legrand, Kyriakos Efthymiadis, Diederik M. Roijers, Ann Nowé
Deep Multi-agent Reinforcement Learning in a Homogeneous Open Population. BNCAI (2018)
Jie Jiang, Mark Hoogendoorn, Qiuqiang Kong, Diederik M. Roijers, Nigel Gilbert
Predicting Appliance Usage Status In Home Like Environments. DSL (2018)
Luisa M. Zintgraf, Diederik M. Roijers, Sjoerd Linders, Catholijn M. Jonker, Ann Nowé
Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making. CoRR (2018)
Gongjin Lan, Milan Jelisavcic, Diederik M. Roijers, Evert Haasdijk, A. E. Eiben
Directed Locomotion for Modular Robots with Evolvable Morphologies. PPSN (1) (2018)
Diederik M. Roijers, Erwin Walraven, Matthijs T. J. Spaan
Bootstrapping LPs in Value Iteration for Multi-Objective and Partially Observable MDPs. ICAPS (2018)
Diederik M. Roijers, Luisa M. Zintgraf, Ann Nowé
Interactive Thompson Sampling for Multi-objective Multi-armed Bandits. ADT (2017)
Denis Steckelmacher, Diederik M. Roijers, Anna Harutyunyan, Peter Vrancx, Ann Nowé
Reinforcement Learning in POMDPs with Memoryless Options and Option-Observation Initiation Sets. CoRR (2017)
Pieter Libin, Timothy Verstraeten, Kristof Theys, Diederik M. Roijers, Peter Vrancx, Ann Nowé
Efficient Evaluation of Influenza Mitigation Strategies Using Preventive Bandits. AAMAS Workshops (Visionary Papers) (2017)
Pieter Libin, Timothy Verstraeten, Diederik M. Roijers, Jelena Grujic, Kristof Theys, Philippe Lemey, Ann Nowé
Bayesian Best-Arm Identification for Selecting Influenza Mitigation Strategies. CoRR (2017)
Ayumi Igarashi, Diederik M. Roijers
Multi-criteria Coalition Formation Games. ADT (2017)
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)
Joost van Doorn, Daan Odijk, Diederik M. Roijers, Maarten de Rijke
Balancing Relevance Criteria through Multi-Objective Optimization. SIGIR (2016)
Diederik M. Roijers
Multi-objective decision-theoretic planning: abstract. AI Matters 2 (4) (2016)
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)

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Publication Activity (10 Years)

Top Topics

Top Venues

Diederik M. Roijers