Books

Diederik M. Roijers and Shimon Whiteson - Multi-Objective Decision Making. In the series: Synthesis Lectures on Artificial Intelligence and Machine Learning 11:1, Morgan and Claypool, April 2017. ISBN: 9781627059602 (paperback) / 9781627056991 (e-book). [link]

Journal articles

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. In Autonomous Agents and Multi-Agent, to appear in 2022. [preprint]

Willem Röpke, Diederik M. Roijers, Ann Nowé, and Roxana Rădulescu - On nash equilibria in normal-form games with vectorial payoffs. In Autonomous Agents and Multi-Agent , 36, Article number: 53 (2022) [link]

Willem Röpke, Diederik M. Roijers, Ann Nowé, and Roxana Rădulescu - Preference Communication in Multi-Objective Normal-Form Games. In Neural Computing and Applications (2022), 2022. [preprint]

Conor F. Hayes, Roxana Rădulescu, 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 Ramos, Marcello Restelli, Peter Vamplew, and Diederik M. Roijers. In Autonomous Agents and Multi-Agent Systems, volume 36, Article number: 26 (2022) [open access]

Roxana Rădulescu, Timothy Verstraeten, Yijie Zhang, Patrick Mannion, Diederik M. Roijers, and Ann Nowé - Opponent learning awareness and modelling in multi-objectivenormal form games. In Neural Computing and Applications 2021: 1-23 [pdf]

Gongjin Lan, Matteo De Carlo, Fuda van Diggelen, Jakub M. Tomczak, Diederik M. Roijers, and Agoston E. Eiben. Learning directed locomotion in modular robots with evolvable morphologies. In Applied Soft Computing 2021: 107688 [html]

Jiang, Jie, Qiuqiang Kong, Mark D. Plumbley, Nigel Gilbert, Mark Hoogendoorn, and Diederik M. Roijers - Deep Learning-Based Energy Disaggregation and On/Off Detection of Household Appliances. in ACM Transactions on Knowledge Discovery from Data (TKDD) 15, no. 3: 1-21, 2021 [html]

Eugenio Bargiacchi, Diederik M. Roijers, and Ann Nowé - AI-Toolbox: A C++ library for Reinforcement Learning and Planning (with Python Bindings). Journal of Machine Learning Research (JMLR) 21(102): 1−12, 2020. [pdf] [code]

Timothy Verstraeten, Eugenio Bargiacchi, Pieter J.K. Libin, Jan Helsen, Diederik M. Roijers, Ann Nowé - Multi-Agent Thompson Sampling for Bandit Applications with Sparse Neighbourhood Structures. Nature: Scientific Reports vol. 10, no. 1 (2020): 1-13. [online pdf]

Roxana Rădulescu, Patrick Mannion, Yijie Zhang, Diederik M. Roijers, Ann Nowé - A Utility-Based Analysis of Equilibria in Multi-Objective Normal Form Games. Knowledge Engineering Review, 2020. [preprint]

Roxana Rădulescu, Patrick Mannion, Diederik M. Roijers, Ann Nowé - Multi-Objective Multi-Agent Decision Making: A Utility-based Analysis and Survey. Autonomous Agents and Multi-Agent Systems (JAAMAS), 34, 10 (2020). Special issue on New Horizons in Multiagent Learning. [pdf] [video]

Felipe Leno Da Silva, Cyntia E.H. Nishida, Diederik M. Roijers, Anna H. Reali Costa - Coordination of Electric Vehicle Charging through Multiagent Reinforcement Learning. IEEE Transactions on Smart Grid vol. 11, no. 3, pp. 2347-2356, May 2020. [pdf]

Shiyu Zhang, Sander Bakkes, Diederik M. Roijers, and Pieter Spronck - Avatars of a Feather Flock Together: Gender Homophily in Online Video Games Revealed via Exponential Random Graph (ERG) Modeling. IEEE Transactions on Games. vol. 12, no. 1, pp. 86-100, March 2020 [pdf]

Stephane Doncieux, David Filliat, Natalia Diaz-Rodriguez, Tim Hospedales, Richard Duro, Alexandre Coninx, Diederik M. Roijers, Benoît Girard, Nicolas Perrin, Olivier Sigaud - Open-ended Learning: a Conceptual Framework based on Representational Redescription. Frontiers in Neurorobotics, 12:59-64, 25 September 2018. [pdf]

Diederik M. Roijers, Shimon Whiteson, and Frans Oliehoek - Computing Convex Coverage Sets for Faster Multi-Objective Coordination. Journal of Artificial Intelligence Research (JAIR) , 52:399–443, 2015. [pdf] [bib]

Diederik M. Roijers, Peter Vamplew, Shimon Whiteson, and Richard Dazeley - A Survey of Multi-Objective Sequential Decision-Making. Journal of Artificial Intelligence Research (JAIR), 48:67–113, 2013. [pdf] [bib]

Dissertation

Diederik M. Roijers - Multi-Objective Decision-Theoretic Planning, University of Amsterdam, 2016. [pdf] [bib]

Conference papers

Ramon Petri, Eugenio Bargiacchi, Huib Aldewereld and Diederik M. Roijers - Heuristic Coordination in Cooperative Multi-Agent Reinforcement Learning. In: BNAIC/BENELEARN 2021, to appear, November 2021. [pdf]

Eugenio Bargiacchi, Timothy Verstraeten and Diederik M. Roijers - Cooperative Prioritized Sweeping. In: AAMAS 2021: Proceedings of the 20th International Joint Conference on Autonomous Agents and Multi-Agent Systems, pages 160-168, May 2021. [pdf]

Timothy Verstraeten, Pieter-Jan Daems, Eugenio Bargiacchi, Diederik M. Roijers, Pieter Libin and Jan Helsen - Scalable Optimization for Wind Farm Control using Coordination Graphs. In: AAMAS 2021: Proceedings of the 20th International Joint Conference on Autonomous Agents and Multi-Agent Systems, pages 1362-1370, May 2021. [pdf]

Diederik M. Roijers, Luisa M. Zintgraf, Pieter Libin, Mathieu Reymond, Eugenio Bargiacchi and Ann Nowé - Interactive Multi-Objective Reinforcement Learning in Multi-Armed Bandits with Gaussian Process Utility Models. In ECML-PKDD 2020: Proceedings of the 2020 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, September 2020. [pdf] [video]

Xiaodong Nian, Athirai A. Irissappane, Diederik M. Roijers - DCRAC: Deep Conditioned Recurrent Actor-Critic for Multi-Objective Partially Observable Environments. In: AAMAS 2020: Proceedings of the Nineteenth International Joint Conference on Autonomous Agents and Multi-Agent Systems, pages 931-938, May 2020. [pdf] [video]

Hélène Plisnier, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé - Transfer Reinforcement Learning across Environment Dynamics with Multiple Advisors. In BNAIC 2019: Proceedings of the 31st Benelux Conference on Artificial Intelligence Brussels, November 2019. [pdf]

Pieter Libin, Timothy Verstraeten, Diederik M. Roijers, Wenjia Wang, Kristof Theys and Ann Nowé - Bayesian Anytime m-top Exploration. In Proceedings of the IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), Portland, Oregon (USA), 4-6 November 2019.

Denis Steckelmacher, Hélène Plisnier, Diederik M. Roijers, and Ann Nowé - Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics. In ECML-PKDD 2019: Proceedings of the 2019 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Würzburg, September 2019. [pdf] [code]

Axel Abels, Diederik M. Roijers, Tom Lenaerts, Ann Nowé, Denis Steckelmacher - Dynamic Weights in Multi-Objective Deep Reinforcement Learning. In ICML2019: Proceedings of the Thirty-sixth International Conference on Machine Learning. Long Beach (USA), June 2019. [pdf] [code]

Marysia Winkels, Diederik M. Roijers, Maarten van Someren, Emi Yamamoto, Richard Pronk, Edwin Odijk and Maarten de Jonge - Challenge Balancing for a Kanji E-Tutoring System. In BNAIC 2018: Proceedings of the 30th Benelux Conference on Artificial Intelligence, ‘s-Hertogenbosch, November 2018. [pdf]

Roxana Rădulescu, Manon Legrand, Kyriakos Efthymiadis, Diederik M. Roijers and Ann Nowé - Deep Multi-Agent Reinforcement Learning in a Homogeneous Open Population. In BNAIC 2018: Proceedings of the 30th Benelux Conference on Artificial Intelligence, ‘s-Hertogenbosch, November 2018. [pdf]

Pieter Libin, Timothy Verstraeten, Diederik M. Roijers, Jelena Grujic, Kristof Theys, Philippe Lemey, and Ann Nowé - Bayesian Best-Arm Identification for Selecting Influenza Mitigation Strategies. In ECML-PKDD 2018: Proceedings of the 2018 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Dublin, September 2018. [extended version (pdf)]

Gongjin Lan, Jesús Benito-Picazo, Diederik M. Roijers, Enrique Domínguez, A.E. Eiben - Real-time Robot Vision on Low-performance Computing Hardware. In ICARCV 2018, Singapore, 2018. [pdf]

Eugenio Bargiacchi, Timothy Verstraeten, Diederik M. Roijers, Ann Nowé and Hado van Hasselt - Learning to Coordinate with Coordination Graphs in Repeated Single-Stage Multi-Agent Decision Problems. In ICML 2018, Stockholm, July 2018. [pdf]

Jie Jiang, Mark Hoogendoorn, Qiuqiang Kong, Diederik M. Roijers and Nigel Gilbert - Predicting Appliance Usage Status In Home-like Environments. In 23rd International Conference on Digital Signal Processing (DSP 2018), 2018.

Gongjin Lan, Milan Jelisavcic, Diederik M. Roijers, Evert Haasdijk, and A.E. Eiben - Directed Locomotion for Modular Robots with Evolvable Morphologies. In PPSN 2018, Coimbra, September 2018. [pdf]

Milan Jelisavcic, Diederik M. Roijers, and A.E. Eiben - Analysing the Relative Importance of Robot Brains and Bodies. In ALIFE 2018 , July 2018. [pdf]

Diederik M. Roijers, Erwin Walraven and Matthijs T.J. Spaan - Bootstrapping LPs in Value Iteration for Multi-Objective and Partially Observable MDPs. In ICAPS 2018: Proceedings of the Twenty-Eighth International Conference on Automated Planning and Scheduling, June 2018. [pdf]

Luisa M. Zintgraf, Diederik M. Roijers, Sjoerd Linders, Catholijn M. Jonker, and Ann Nowé - Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making. In AAMAS 2018: Proceedings of the Seventeenth International Joint Conference on Autonomous Agents and Multi-Agent Systems, July 2018. [pdf]

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. In Proceedings of the 32th AAAI Conference on Artificial Intelligence, February 2018. [pdf]

Diederik M. Roijers, Luisa M. Zintgraf, and Ann Nowé - Interactive Thompson Sampling for Multi-Objective Multi-Armed Bandits. In Proceedings of the 5th International Conference on Algorithmic Decision Theory (ADT), October 2017. [pdf]

Ayumi Igarashi and Diederik M. Roijers - Multi-Criteria Coalition Formation Games. In Proceedings of the 5th International Conference on Algorithmic Decision Theory (ADT), October 2017. [pdf]

Luisa M. Zintgraf, Edgar A. Lopez-Rojas, Diederik M. Roijers, Ann Nowé - MultiMAuS: a Multi-modal Authentication Simulator for Fraud Detection Research. In Proceedings of the European Modeling and Simulation Symposium (EMSS), September 2017. [pdf]

Maarten de Waard, Diederik M. Roijers and Sander C.J. Bakkes - Monte Carlo Tree Search with Options for General Video Game Playing. In Proceedings of the 2016 IEEE Conference on Computational Intelligence and Games, September 2016. [pdf]

Joost van Doorn, Daan Odijk, Diederik M. Roijers, and Maarten de Rijke - Balancing Relevance Criteria through Multi-Objective Optimization. In Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, July 2016. [pdf] [bib]

Joris Scharpff, Diederik M. Roijers, Frans A. Oliehoek, Matthijs T.J. Spaan and Mathijs de Weerdt - Solving Transition-Independent Multi-agent MDPs with Sparse Interactions. In Proceedings of the 30th AAAI Conference on Artificial Intelligence, May 2016. [pdf] [bib]

Diederik M. Roijers, Shimon Whiteson, and Frans Oliehoek - Point-Based Planning for Multi-Objective POMDPs. In IJCAI 2015: Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, pp. 1666-1672, July 2015. [pdf] [bib]

Luisa M. Zintgraf, Timon V. Kanters, Diederik M. Roijers, Frans A. Oliehoek, and Philipp Beau - Quality Assessment of MORL Algorithms: A Utility-Based Approach. In Benelearn 2015: Proceedings of the Twenty-Fourth Belgian-Dutch Conference on Machine Learning, June 2015. [pdf] [bib]

Mircea Traichioiu, Sander Bakkes and Diederik M. Roijers - Grammar-based Procedural Content Generation from Designer-provided Difficulty Curves. In FDG2015: Proceedings of the Foundations of Digital Games conference, June 2015. [pdf] [bib]

Alex Rietveld, Sander Bakkes, and Diederik M. Roijers - Circuit-Adaptive Challenge Balancing in Racing Games. In GEM 2014: IEEE Games, Entertainment, and Media, pp. 54-61, October 2014. [pdf] [bib]

Paris Mavromoustakos Blom, Sander Bakkes, Chek Tien Tan, Shimon Whiteson, Diederik M. Roijers, Roberto Valenti and Theo Gevers - Towards Personalised Gaming via Facial Expression Recognition. In AIIDE-14: Proceedings of the Tenth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment , pp. 30-36, October 2014. [pdf] [bib]

Maarten Inja, Chiel Kooijman, Maarten de Waard, Diederik M. Roijers, and Shimon Whiteson - Queued Pareto Local Search for Multi-Objective Optimization. In PPSN 2014: Proceedings of the Thirteenth International Conference on Parallel Problem Solving from Nature, pp. 589–599, September 2014. [pdf] [bib]

Diederik M. Roijers, Joris Scharpff, Matthijs T.J. Spaan, Frans A. Oliehoek, Mathijs De Weerdt, and Shimon Whiteson - Bounded Approximations for Linear Multi-Objective Planning under Uncertainty. In ICAPS 2014: Proceedings of the Twenty-Fourth International Conference on Automated Planning and Scheduling, pp. 262–270, June 2014. [pdf] [bib]

Diederik M. Roijers, Shimon Whiteson, and Frans Oliehoek - Linear Support for Multi-Objective Coordination Graphs. In AAMAS 2014: Proceedings of the Thirteenth International Joint Conference on Autonomous Agents and Multi-Agent Systems, pp. 1297-1304, May 2014. [pdf] [bib]

Diederik M. Roijers, Shimon Whiteson, and Frans A. Oliehoek - Computing Convex Coverage Sets for Multi-Objective Coordination Graphs. In ADT 2013: Proceedings of the Third International Conference on Algorithmic Decision Theory, pp. 309–323, November 2013. [pdf] [bib]

Diederik M. Roijers, Johan Jeuring and Ad Feelders - Probability estimation and a competence model for rule based e-tutoring systems, In Proceedings of LAK12: 2nd International Conference on Learning Analytics and Knowledge, pp. 255-258, April 29 - May 2, 2012. [pdf] [bib]

Demonstrations and Extended Abstracts

Jeff van de Kamer, Maaike Hovenkamp, Erik Puik and Diederik M. Roijers - Monitoring Diabetic Foot Ulceration Treatment with Smart Insoles and Neural Networks. In BNAIC/BeNeLearn 2022, Mechelen, November 2022. (Demonstration) [pdf]

Willem Röpke, Diederik M. Roijers, Roxana Rădulescu and Ann Nowé - Communication In Multi-Objective Games. In BNAIC/BeNeLearn 2022, Mechelen, November 2022. (Thesis Abstract) [pdf]

Conor F Hayes, Timothy Verstraeten, Diederik M. Roijers, Enda Howley and Patrick Mannion - Expected scalarised returns dominance: a new solution concept for multi-objective decision making. In BNAIC/BeNeLearn 2022, Mechelen, November 2022. (Extended Abstract) [pdf]

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 Ramos, Marcello Restelli, Peter Vamplew and Diederik M. Roijers - Abstract: A Practical Guide to Multi-Objective Reinforcement Learning and Planning. In BNAIC/BeNeLearn 2022, Mechelen, November 2022. (Extended Abstract) [pdf]

Raphaël Avalos, Mathieu Reymond, Ann Nowé, and Diederik M. Roijers - Local Advantage Networks for Cooperative Multi-Agent Reinforcement Learning. In Proceedings of the 21st International Joint Conference on Autonomous Agents and Multiagent Systems, pages 1524-1527, May 2022. (Extended Abstract) [pdf]

Shang Wang, Mathieu Reymond, Athirai A. Irissappane, and Diederik M. Roijers - Near On-Policy Experience Sampling in Multi-Objective Reinforcement Learning. In Proceedings of the 21st International Joint Conference on Autonomous Agents and Multiagent Systems, pages 1756-1759, May 2022. (Extended Abstract) [pdf]

Conor F. Hayes, Diederik M. Roijers, Enda Howley, and Patrick Mannion - Decision-Theoretic Planning for the Expected Scalarised Returns. In Proceedings of the 21st International Joint Conference on Autonomous Agents and Multiagent Systems, pages 1621-1624, May 2022. (Extended Abstract) [pdf]

Conor F Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley and Patrick Mannion - Distributional Monte Carlo Tree Search for Risk-Aware and Multi-Objective Reinforcement Learning. In: AAMAS 2021: Proceedings of the 20th International Joint Conference on Autonomous Agents and Multi-Agent Systems, pages 1530-1533, May 2021. [pdf]

Yijie Zhang, Roxana Rădulescu, Patrick Mannion, Diederik M. Roijers, Ann Nowé - Opponent Modelling for Reinforcement Learning in Multi-Objective Normal Form Games, In Proceedings of the Nineteenth International Joint Conference on Autonomous Agents and Multiagent Systems, pages 2080-2082, May 2020. (Extended Abstract) [pdf]

Roxana Rădulescu, Patrick Mannion, Diederik M. Roijers, Ann Nowé - Multi-Objective Multi-Agent Decision Making: A Utility-based Analysis and Survey, In Proceedings of the Nineteenth International Joint Conference on Autonomous Agents and Multiagent Systems, pages 2158-2160, May 2020. (Extended Abstract - Journal Track) [pdf]

Timothy Verstraeten, Eugenio Bargiacchi, Pieter J.K. Libin, Diederik M. Roijers, and Ann Nowé - Opponent Modelling for Reinforcement Learning in Multi-Objective Normal Form Games, In Proceedings of the Nineteenth International Joint Conference on Autonomous Agents and Multiagent Systems, pages 2029-2031, May 2020. (Extended Abstract) [pdf]

Denis Steckelmacher, Hélène Plisnier, Diederik M. Roijers, Ann Nowé - Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics. In BNAIC 2019, 2 pages, November 2019. (Extended abstract) [pdf]

Pieter Libin, Timothy Verstraeten, Diederik M. Roijers, Wenjia Wang, Kristof Theys, Ann Nowé - Thompson Sampling for m-top Exploration. In BNAIC 2019, 2 pages, November 2019. (Extended abstract) [pdf]

Mark de Blaauw, Diederik M. Roijers, Vesa Muhonen - A Scalable Logo Recognition Model with Deep Meta-Learning. In BNAIC 2019, 2 pages, November 2019. (MSc Thesis abstract) [pdf]

Axel Abels, Diederik M. Roijers, and Tom Lennaerts - Thesis Abstracht: Dynamic Weights in Multi-Objective Deep Reinforcement Learning. In BNAIC 2018, 2 pages, November 2018. (Extended abstract) [pdf] [Best Thesis Abstract Award]

Peter Vamplew, Dean Webb, Luisa M. Zintgraf, Diederik M. Roijers, Richard Dazeley, Rustam Issabekov, and Evan Dekker - MORL-Glue: A Benchmark Suite for Multi-Objective Reinforcement Learning. In BNAIC 2017, 2 pages, November 2017. (Demonstration paper) [pdf]

Denis Steckelmacher, Hélène Plisnier, Diederik M. Roijers, and Ann Nowé - Hierarchical Reinforcement Learning for a Robotic Partially Observable Task. In BNAIC 2017, 2 pages, November 2017. (Demonstration paper), 2 pages, November 2017. [pdf] [Best Demo Award]

Manon Legrand, Roxana Rădulescu, Diederik M. Roijers, and Ann Nowé - Neural Network Reuse in Deep RL for Autonomous Vehicles among Human Drivers. In BNAIC 2017, 2 pages, November 2017. (Extended abstract) [pdf]

Manon Legrand, Roxana Rădulescu, Diederik M. Roijers, and Ann Nowé - The SimuLane Highway Traffic Simulator for Multi-Agent Reinforcement Learning. In BNAIC 2017, 2 pages, November 2017. (Demonstration paper) [pdf]

Joost van Doorn, Daan Odijk, Diederik M. Roijers, and Maarten de Rijke - Multi-Objective Optimization for Information Retrieval, In Proceedings of the 28th Belgium-Netherlands Artificial Intelligence Conference, November 2016. (Extended Abstract) [pdf]

Joris Scharpff, Diederik M. Roijers, Frans A. Oliehoek, Matthijs T. J. Spaan, and Mathijs M. de Weerdt - Conditional Return Policy Search for TI-MMDPs with Sparse Interactions, In Proceedings of the 28th Belgium-Netherlands Artificial Intelligence Conference, November 2016. (Extended Abstract) [pdf]

Diederik M. Roijers - Abstract: Multi-Objective Decision-Theoretic Planning. In AI Matters, page 11-12, Volume 2, Issue 4, Summer 2016. [pdf]

Auke J. Wiggers, Frans A. Oliehoek, and Diederik M. Roijers - Structure in the Value Function of Two-Player Zero-Sum Games of Incomplete Information. In Proceedings of the 22nd European Conference on Artificial Intelligence, August 2016. (Extended Abstract) [pdf]

Maarten de Waard, Maarten Inja, Chiel Kooijman, Diederik M. Roijers, and Shimon Whiteson - Queued Pareto Local Search for Multi-objective Decision Making, In Proceedings of the 27th Belgium-Netherlands Artificial Intelligence Conference, November 2015. (Extended Abstract) [pdf] [bib]

Diederik M. Roijers - Efficient Methods for Multi-Objective Decision-Theoretic Planning. In IJCAI 2015: Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, July 2015. (Doctoral Consortium) [pdf]

Diederik M. Roijers, Joris Scharpff, Matthijs T.J. Spaan, Frans A. Oliehoek, Mathijs De Weerdt, and Shimon Whiteson - Bounded Approximations for Linear Multi-Objective Planning under Uncertainty. In Proceedings of the 26th Belgium-Netherlands Artificial Intelligence Conference, November 2014. (Extended Abstract) [pdf]

Paris Mavromoustakos Blom, Sander Bakkes and Diederik M. Roijers - Using Facial Expressions for Personalised Gaming. In Proceedings of the 26th Belgium-Netherlands Artificial Intelligence Conference, November 2014. (Demo) [pdf]

Diederik M. Roijers - Convex Coverage Set Methods for Multi-Objective Collaborative Decision Making. In AAMAS 2014: Proceedings of the Thirteenth International Joint Conference on Autonomous Agents and Multi-Agent Systems, pp. 1727-1728, May 2014. (Doctoral Consortium) [pdf] [bib]

Eugenio Bargiacchi, Camiel R. Verschoor, Guangliang Li, and Diederik M. Roijers - Decentralized Solutions and Tactics for RTS, In Proceedings of the 25th Belgium-Netherlands Artificial Intelligence Conference, pp. 272-273, 7-8 November 2013. (Demo) [pdf] [bib]

Diederik M. Roijers, Shimon Whiteson, and Frans A. Oliehoek - Multi-Objective Variable Elimination for Collaborative Graphical Games, In Proceedings of the Twelfth International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 1209–1210, May 2013. (Extended Abstract) [pdf] [bib]

Workshop papers

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. In ASSETS'22 workshop on The Future of Urban Accessibility, Athens, October 2022. [link]

Raphaël Avalos, Mathieu Reymond, Ann Nowé, and Diederik M. Roijers - Local Advantage Networks for Multi-Agent Reinforcement Learning in Dec-POMDPs. In European Workshop on Reinforcement Learning (EWRL 2022), Milan, 2022. [pdf]

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. In European Workshop on Reinforcement Learning (EWRL 2022), Milan, 2022. [pdf]

Eugenio Bargiacchi, Raphaël Avalos, Timothy Verstraeten, Pieter Libin, Ann Nowé and Diederik M. Roijers - Multi-agent RMax for Multi-Agent Multi-Armed Bandits. In Proceedings of the Adaptive and Learning Agents Workshop 2022 (ALA-22) at AAMAS, 2022. [pdf] [video]

Willem Röpke, Roxana Radulescu, Ann Nowe and Diederik M. Roijers - Commitment and Cyclic Strategies in Multi-Objective Games. In Proceedings of the Adaptive and Learning Agents Workshop 2022 (ALA-22) at AAMAS, 2022. [pdf] [video]

Conor F. Hayes, Diederik M. Roijers, Enda Howley and Patrick Mannion - Multi-Objective Distributional Value Iteration. In Proceedings of the Adaptive and Learning Agents Workshop 2022 (ALA-22) at AAMAS, 2022. [pdf] [video]

Willem Röpke, Diederik M. Roijers, Ann Nowé and Roxana Rădulescu - On Nash Equilibria for Multi-Objective Normal Form Games under Scalarised Expected Returns versus Expected Scalarised Returns Proceedings of the first Multi-Objective Decision Making workshop (MODeM-2021), 2021. [pdf] [video]

Mathieu Reymond, Conor F. Hayes, Diederik M. Roijers, Denis Steckelmacher and Ann Nowé - Actor-Critic Multi-Objective Reinforcement Learning for Non-Linear Utility Functions Proceedings of the first Multi-Objective Decision Making workshop (MODeM-2021), 2021. [pdf] [video]

Diederik M. Roijers, Willem Röpke, Ann Nowé and Roxana Rădulescu - On Following Pareto-Optimal Policies in Multi-Objective Planning and Reinforcement Learning Proceedings of the first Multi-Objective Decision Making workshop (MODeM-2021), 2021. [pdf] [video]

Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley and Patrick Mannion - Risk-Aware and Multi-Objective Decision Making with Distributional Monte Carlo Tree Search. Proceedings of the Adaptive and Learning Agents Workshop 2021 (ALA-21) at AAMAS, 2021. [pdf] [video]

Willem Röpke, Roxana Rădulescu, Diederik Roijers and Ann Nowé - Communication Strategies in Multi-Objective Normal-Form Games. Proceedings of the Adaptive and Learning Agents Workshop 2021 (ALA-21) at AAMAS, 2021. [pdf] [video]

Conor F. Hayes, Timothy Verstraeten, Diederik M. Roijers, Enda Howley and Patrick Mannion - Dominance Criteria and Solution Sets for the Expected Scalarised Returns. Proceedings of the Adaptive and Learning Agents Workshop 2021 (ALA-21) at AAMAS, 2021. [pdf] [video]

Deep Reinforcement Learning for Solving Train Unit Shunting Problem with Interval Timing - Wan-Jui Lee, Helia Jamshidi and Diederik M. Roijers. Artificial Intelligence for RAILwayS at EDCC, in Proceedings of the European Dependable Computing Conference, CCIS, volume 1279, pp. 99-110. [pdf]

Yijie Zhang, Roxana Radulescu, Patrick Mannion, Diederik M. Roijers and Ann Nowé - Opponent Modelling using Policy Reconstruction for Multi-Objective Normal Form Games. Proceedings of the Adaptive and Learning Agents Workshop 2020 (ALA-20) at AAMAS, 2020. [pdf]

Timothy Verstraeten, Eugenio Bargiacchi, Pieter Libin, Jan Helsen, Diederik M. Roijers and Ann Nowé - Thompson Sampling for Loosely-Coupled Multi-Agent Systems: An Application to Wind Farm Control. Proceedings of the Adaptive and Learning Agents Workshop 2020 (ALA-20) at AAMAS, 2020. [pdf]

Roxana Rădulescu, Patrick Mannion, Diederik M. Roijers, and Ann Nowé - Equilibria in Multi-Objective Games: a Utility-Based Perspective. In Proceedings of the Adaptive and Learning Agents Workshop 2019 (ALA-19) at AAMAS, 2019. [pdf]

Pieter Libin, Timothy Verstraeten, Diederik M. Roijers, Wenjia Wang, Kristof Theys and Ann Nowé - Boundary Focused Thompson Sampling. In: Proceedings of the Adaptive and Learning Agents Workshop 2019 (ALA-19) at AAMAS, 2019. [Please see conference version, ICTAI 2019]

Hélène Plisnier, Denis Steckelmacher, Tim Brys, Diederik M. Roijers and Ann Nowé - Directed Policy Gradient for Safe Reinforcement Learning with Human Advice, In EWRL 2018, Lille. [pdf]

Denis Steckelmacher, Hélène Plisnier, Diederik M. Roijers and Ann Nowé - Stable, Practical and On-line Bootstrapped Conservative Policy Iteration, In EWRL 2018, Lille. [pdf]

Diederik M. Roijers, Luisa M. Zintgraf, Pieter Libin, and Ann Nowé - Interactive Multi-Objective RL in Multi-Armed Bandits for Any Utility Function. In ALA workshop at ICML/AAMAS/IJCAI 2018, 8 pages, July 2018. [pdf] [Best Paper Award]

Diederik M. Roijers, Denis Steckelmacher, and Ann Nowé - Multi-objective Reinforcement Learning for the Expected Utility of the Return. In ALA workshop at ICML/AAMAS/IJCAI 2018, 8 pages, July 2018. [pdf]

Denis Steckelmacher, Hélène Plisnier, Diederik M. Roijers, and Ann Nowé - Hierarchical Reinforcement Learning for Robots in POMDPs with Option-Observation Initiation Sets. In Proceedings of Delft Workshop on Robot Learning (DWRL), 3 pages, September 2017. [pdf]

Ayumi Igarashi and Diederik M. Roijers - Multi-Criteria Coalition Formation Games. In Proceedings of 8th AAMAS Workshop on Cooperative Games in Multiagent Systems (CoopMAS), 15 pages, May 2017. [pdf]

Pieter Libin, Timothy Verstraeten, Kristof Theys, Diederik M. Roijers, Peter Vrancx, and Ann Nowé - Efficient evaluation of influenza mitigation strategies using preventive bandits. In Proceedings of the AAMAS workshop on Adaptive Learning Agents (ALA), 9 pages, May 2017.

Hossam Mossalam, Yannis Assael, Diederik M. Roijers, and Shimon Whiteson - Multi-Objective Deep Reinforcement Learning. In Proceedings of the NIPS workshop on Deep Reinforcement Workshop, Barcelona, December 2016.

Diederik M. Roijers, Shimon Whiteson, Alex Ihler, and Frans A. Oliehoek - Variational Multi-Objective Coordination, In Proceedings of the 2015 NIPS workshop: Learning, Inference and Control of Multi-Agent Systems, December 2015. [pdf] [bib]

Diederik M. Roijers‚ Shimon Whiteson‚ Peter Vamplew and Richard Dazeley - Why Multi−Objective Reinforcement Learning?. In EWRL 2015: Proceedings of the Twelfth European Workshop on Reinforcement Learning, July 2015. [pdf] [bib]

Joris Scharpff, Diederik M. Roijers, Frans A. Oliehoek, Matthijs T.J. Spaan and Mathijs de Weerdt - Solving Multi-agent MDPs Optimally with Conditional Return Graphs. In Proceedings of the Tenth AAMAS Workshop on Multi-Agent Sequential Decision Making in Uncertain Domains (MSDM), May 2015. [pdf] [bib]

Auke J. Wiggers, Frans A. Oliehoek, and Diederik M. Roijers - Structure in the value function of zero-sum games of incomplete information. In Proceedings of the Tenth AAMAS Workshop on Multi-Agent Sequential Decision Making in Uncertain Domains (MSDM), May 2015. [pdf] [bib]

Chiel Kooijman, Maarten de Waard, Maarten Inja, Diederik M. Roijers, and Shimon Whiteson - Pareto Local Policy Search for MOMDP Planning. In ESANN 2015: Special Session on Emerging Techniques and Applications in Multi-Objective Reinforcement Learning at the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning 2015, pp. 53-58, April 2015. [pdf] [bib]

Master's thesis

Diederik M. Roijers - Probability estimation and competence models for rule and strategy based e-tutoring systems, Master's thesis Applied Computing Science, Utrecht University, June 2011 [pdf] [bib]

ArXiv pre-prints

Willem Röpke, Diederik M. Roijers, Ann Nowé, Roxana Rădulescu - Preference Communication in Multi-Objective Normal-Form Games, 2021 [link]

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, 2021 [link]

Conor F. Hayes, Roxana Rădulescu, 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 Ramos, Marcello Restelli, Peter Vamplew, and Diederik M. Roijers - A Practical Guide to Multi-Objective Reinforcement Learning and Planning, 2021 [link]

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, 2021 [link]

Eugenio Bargiacchi, Timothy Verstraeten, Diederik M. Roijers, Ann Nowé - Model-based Multi-Agent Reinforcement Learning with Cooperative Prioritized Sweeping, 2020 [link]

Hossam Mossalam, Yannis Assael, Diederik M. Roijers, and Shimon Whiteson - Multi-Objective Deep Reinforcement Learning, 2016 [link]

Auke J. Wiggers, Frans A. Oliehoek, and Diederik M. Roijers - Structure in the Value Function of Two-Player Zero-Sum Games of Incomplete Information. ArXiv e-prints, arXiv:1606.06888, June 2016. [link]

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

Jocular

Roxanne van der Pol, Brian van der Bijl, Diederik M. Roijers - Faking Ancient Computer Science: a Special SIGBOVIK Tutorial. In: A Record of the Proceedings of SIGBOVIK 2020, online, 2020 [pdf]