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- affiliation: Vrije Universiteit Brussel, Artificial Intelligence Lab, Belgium
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Journal Articles
- 2024
[j76]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: 123686 (2024)- [j75]Gaoyuan Liu, Joris De Winter, Yuri Durodié, Denis Steckelmacher, Ann Nowé, Bram Vanderborght:
Optimistic Reinforcement Learning-Based Skill Insertions for Task and Motion Planning. IEEE Robotics Autom. Lett. 9(6): 5974-5981 (2024) - [j74]Arnau Dillen, Mohsen Omidi, Fakhreddine Ghaffari, Olivier Romain, Bram Vanderborght, Bart Roelands, Ann Nowé, Kevin De Pauw:
User Evaluation of a Shared Robot Control System Combining BCI and Eye Tracking in a Portable Augmented Reality User Interface. Sensors 24(16): 5253 (2024) - [j73]Diana Gomes, Kyriakos Efthymiadis, Ann Nowé, Peter Vrancx:
Depth Scaling in Graph Neural Networks: Understanding the Flat Curve Behavior. Trans. Mach. Learn. Res. 2024 (2024) - 2023
- [j72]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): 23 (2023) - [j71]Axel Abels, Tom Lenaerts, Vito Trianni, Ann Nowé:
Dealing with expert bias in collective decision-making. Artif. Intell. 320: 103921 (2023) - [j70]Nassim Versbraegen, Barbara Gravel, Charlotte Nachtegael, Alexandre Renaux, Emma Verkinderen, Ann Nowé, Tom Lenaerts, Sofia Papadimitriou:
Faster and more accurate pathogenic combination predictions with VarCoPP2.0. BMC Bioinform. 24(1): 179 (2023) - [j69]Alexandre Renaux, Chloé Terwagne, Michael Cochez, Ilaria Tiddi, Ann Nowé, Tom Lenaerts:
A knowledge graph approach to predict and interpret disease-causing gene interactions. BMC Bioinform. 24(1): 324 (2023) - [j68]Gaoyuan Liu, Joris De Winter, Denis Steckelmacher, Roshan Kumar Hota, Ann Nowé, Bram Vanderborght:
Synergistic Task and Motion Planning With Reinforcement Learning-Based Non-Prehensile Actions. IEEE Robotics Autom. Lett. 8(5): 2764-2771 (2023) - [j67]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) - 2022
- [j66]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): 26 (2022) - [j65]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): 53 (2022) - [j64]Charlotte Nachtegael, Barbara Gravel, Arnau Dillen, Guillaume Smits, Ann Nowé, Sofia Papadimitriou, Tom Lenaerts:
Scaling up oligogenic diseases research with OLIDA: the Oligogenic Diseases Database. Database J. Biol. Databases Curation 2022(2022) (2022) - [j63]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): 1759-1781 (2022) - 2021
- [j62]Ulle Endriss, Ann Nowé, Maria L. Gini, Victor R. Lesser, Michael Luck, Ana Paiva, Jaime Simão Sichman:
Autonomous agents and multiagent systems: perspectives on 20 years of AAMAS. AI Matters 7(3): 29-37 (2021) - [j61]Joris De Winter, Ilias El Makrini, Greet Van de Perre, Ann Nowé, Tom Verstraten, Bram Vanderborght:
Autonomous assembly planning of demonstrated skills with reinforcement learning in simulation. Auton. Robots 45(8): 1097-1110 (2021) - [j60]Gianluca Bontempi, Ricardo Chavarriaga, Hans ed Canck, Emanuela Girardi, Holger H. Hoos, Iarla Kilbane-Dawe, Tonio Ball, Ann Nowé, Jose Sousa, Davide Bacciu, Marco Aldinucci, Manlio ed Domenico, Alessandro Saffiotti, Marco Maratea:
The CLAIRE COVID-19 initiative: approach, experiences and recommendations. Ethics Inf. Technol. 23(S1): 127-133 (2021) - [j59]Yannick De Bock, Andres Auquilla, Ellen Bracquené, Ann Nowé, Joost R. Duflou:
The energy saving potential of retrofitting a smart heating system: A residence hall pilot study. Sustain. Comput. Informatics Syst. 31: 100585 (2021) - 2020
- [j58]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): 10 (2020) - [j57]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: 102:1-102:12 (2020) - [j56]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: e32 (2020) - [j55]Gabriel de Oliveira Ramos, Bruno C. da Silva, Roxana Radulescu, Ana L. C. Bazzan, Ann Nowé:
Toll-based reinforcement learning for efficient equilibria in route choice. Knowl. Eng. Rev. 35: e8 (2020) - [j54]Yannick De Bock, Andres Auquilla, Ann Nowé, Joost R. Duflou:
Nonparametric user activity modelling and prediction. User Model. User Adapt. Interact. 30(5): 803-831 (2020) - 2019
- [j53]Oliver Roesler, Ann Nowé:
Action learning and grounding in simulated human-robot interactions. Knowl. Eng. Rev. 34: e13 (2019) - [j52]Alexandre Renaux, Sofia Papadimitriou, Nassim Versbraegen, Charlotte Nachtegael, Simon Boutry, Ann Nowé, Guillaume Smits, Tom Lenaerts:
ORVAL: a novel platform for the prediction and exploration of disease-causing oligogenic variant combinations. Nucleic Acids Res. 47(Webserver-Issue): W93-W98 (2019) - [j51]Joris De Winter, Albert De Beir, Ilias El Makrini, Greet Van de Perre, Ann Nowé, Bram Vanderborght:
Accelerating Interactive Reinforcement Learning by Human Advice for an Assembly Task by a Cobot. Robotics 8(4): 104 (2019) - 2018
- [j50]Yaima Filiberto Cabrera, Rafael Bello Pérez, Ann Nowé:
A New Method For Personnel Selection Based On Ranking Aggregation Using A Reinforcement Learning Approach. Computación y Sistemas 22(2) (2018) - [j49]Sofie De Clercq, Steven Schockaert, Ann Nowé, Martine De Cock:
Modelling incomplete information in Boolean games using possibilistic logic. Int. J. Approx. Reason. 93: 1-23 (2018) - [j48]Huong Thi Thu Vu, Felipe Gomez Marulanda, Pierre Cherelle, Dirk Lefeber, Ann Nowé, Bram Vanderborght:
ED-FNN: A New Deep Learning Algorithm to Detect Percentage of the Gait Cycle for Powered Prostheses. Sensors 18(7): 2389 (2018) - 2017
- [j47]Sofie De Clercq, Kim Bauters, Steven Schockaert, Mihail Mihaylov, Ann Nowé, Martine De Cock:
Exact and heuristic methods for solving Boolean games. Auton. Agents Multi Agent Syst. 31(1): 66-106 (2017) - [j46]Pieter Libin, Ewout Vanden Eynden, Francesca Incardona, Ann Nowé, Antonia Bezenchek, EucoHIV Study Group, Anders Sönnerborg, Anne-Mieke Vandamme, Kristof Theys, Guy Baele:
PhyloGeoTool: interactively exploring large phylogenies in an epidemiological context. Bioinform. 33(24): 3993-3995 (2017) - [j45]Diego S. Comas, Gustavo J. Meschino, Ann Nowé, Virginia Laura Ballarin:
Discovering knowledge from data clustering using automatically-defined interval type-2 fuzzy predicates. Expert Syst. Appl. 68: 136-150 (2017) - [j44]Tim Brys, Anna Harutyunyan, Peter Vrancx, Ann Nowé, Matthew E. Taylor:
Multi-objectivization and ensembles of shapings in reinforcement learning. Neurocomputing 263: 48-59 (2017) - [j43]Aleksander Byrski, Ewelina Swiderska, Jakub Lasisz, Marek Kisiel-Dorohinicki, Tom Lenaerts, Dana Samson, Bipin Indurkhya, Ann Nowé:
Socio-cognitively inspired ant colony optimization. J. Comput. Sci. 21: 397-406 (2017) - 2016
- [j42]Marilyn Bello-García, Rafael Bello, María Matilde García Lorenzo, Ann Nowé:
Personnel Selection in a Competitive Environment. Computación y Sistemas 20(2) (2016) - [j41]Dewan Md. Farid, M. Abdulla Al Mamun, Bernard Manderick, Ann Nowé:
An adaptive rule-based classifier for mining big biological data. Expert Syst. Appl. 64: 305-316 (2016) - [j40]Yann-Michaël De Hauwere, Sam Devlin, Daniel Kudenko, Ann Nowé:
Context-sensitive reward shaping for sparse interaction multi-agent systems. Knowl. Eng. Rev. 31(1): 59-76 (2016) - [j39]Abdel Rodríguez, Peter Vrancx, Ricardo Grau, Ann Nowé:
A reinforcement learning approach to coordinate exploration with limited communication in continuous action games. Knowl. Eng. Rev. 31(1): 77-95 (2016) - [j38]Kevin Tanghe, Anna Harutyunyan, Erwin Aertbeliën, Friedl De Groote, Joris De Schutter, Peter Vrancx, Ann Nowé:
Predicting Seat-Off and Detecting Start-of-Assistance Events for Assisting Sit-to-Stand With an Exoskeleton. IEEE Robotics Autom. Lett. 1(2): 792-799 (2016) - [j37]Sofie De Clercq, Steven Schockaert, Martine De Cock, Ann Nowé:
Solving stable matching problems using answer set programming. Theory Pract. Log. Program. 16(3): 247-268 (2016) - 2015
- [j36]Kieu-Ha Phung, Bart Lemmens, Marnix Goossens, Ann Nowé, Lan Tran, Kris Steenhaut:
Schedule-based multi-channel communication in wireless sensor networks: A complete design and performance evaluation. Ad Hoc Networks 26: 88-102 (2015) - [j35]Peter Vrancx, Pasquale Gurzi, Abdel Rodríguez, Kris Steenhaut, Ann Nowé:
A Reinforcement Learning Approach for Interdomain Routing with Link Prices. ACM Trans. Auton. Adapt. Syst. 10(1): 5:1-5:26 (2015) - 2014
- [j34]Mihail Mihaylov, Karl Tuyls, Ann Nowé:
A decentralized approach for convention emergence in multi-agent systems. Auton. Agents Multi Agent Syst. 28(5): 749-778 (2014) - [j33]Nashat Abughalieh, Kris Steenhaut, Ann Nowé, Alagan Anpalagan:
Turbo codes for multi-hop wireless sensor networks with decode-and-forward mechanism. EURASIP J. Wirel. Commun. Netw. 2014: 204 (2014) - [j32]Kristof Van Moffaert, Ann Nowé:
Multi-objective reinforcement learning using sets of pareto dominating policies. J. Mach. Learn. Res. 15(1): 3483-3512 (2014) - 2013
- [j31]Cosmin Lazar, Stijn Meganck, Jonatan Taminau, David Steenhoff, Alain Coletta, Colin Molter, David Y. Weiss Solís, Robin Duque, Hugues Bersini, Ann Nowé:
Batch effect removal methods for microarray gene expression data integration: a survey. Briefings Bioinform. 14(4): 469-490 (2013) - [j30]Cosmin Lazar, Jonatan Taminau, Stijn Meganck, David Steenhoff, Alain Coletta, David Y. Weiss Solís, Colin Molter, Robin Duque, Hugues Bersini, Ann Nowé:
GENESHIFT: A Nonparametric Approach for Integrating Microarray Gene Expression Data Based on the Inner Product as a Distance Measure between the Distributions of Genes. IEEE ACM Trans. Comput. Biol. Bioinform. 10(2): 383-392 (2013) - 2012
- [j29]Jonatan Taminau, Stijn Meganck, Cosmin Lazar, David Steenhoff, Alain Coletta, Colin Molter, Robin Duque, Virginie de Schaetzen, David Y. Weiss Solís, Hugues Bersini, Ann Nowé:
Unlocking the potential of publicly available microarray data using inSilicoDb and inSilicoMerging R/Bioconductor packages. BMC Bioinform. 13: 335 (2012) - [j28]Dimitri Staessens, Didier Colle, Mario Pickavet, Ann Nowé, Kris Steenhaut, Piet Demeester:
Optimization of common pool resource sharing in multidomain IP-over-WDM networks. Comput. Commun. 35(5): 531-540 (2012) - [j27]Mihail Mihaylov, Yann-Aël Le Borgne, Karl Tuyls, Ann Nowé:
Decentralised reinforcement learning for energy-efficient scheduling in wireless sensor networks. Int. J. Commun. Networks Distributed Syst. 9(3/4): 207-224 (2012) - [j26]Nashat Abughalieh, Kris Steenhaut, Bart Lemmens, Ann Nowé:
A Mutual Algorithm for Optimizing Distributed Source Coding in Wireless Sensor Networks. Int. J. Distributed Sens. Networks 8 (2012) - [j25]Yunierkis Pérez-Castillo, Cosmin Lazar, Jonatan Taminau, Matheus Froeyen, Miguel Ángel Cabrera-Pérez, Ann Nowé:
GA(M)E-QSAR: A Novel, Fully Automatic Genetic-Algorithm-(Meta)-Ensembles Approach for Binary Classification in Ligand-Based Drug Design. J. Chem. Inf. Model. 52(9): 2366-2386 (2012) - [j24]Wajdi Halabi, Kris Steenhaut, Marnix Goossens, Thu-Huong Truong, Ann Nowé:
Hierarchical routing and traffic grooming in IP/MPLS-based ASON/GMPLS multi-domain networks. Photonic Netw. Commun. 23(3): 217-229 (2012) - [j23]Cosmin Lazar, Jonatan Taminau, Stijn Meganck, David Steenhoff, Alain Coletta, Colin Molter, Virginie de Schaetzen, Robin Duque, Hugues Bersini, Ann Nowé:
A Survey on Filter Techniques for Feature Selection in Gene Expression Microarray Analysis. IEEE ACM Trans. Comput. Biol. Bioinform. 9(4): 1106-1119 (2012) - 2011
- [j22]Jonatan Taminau, David Steenhoff, Alain Coletta, Stijn Meganck, Cosmin Lazar, Virginie de Schaetzen, Robin Duque, Colin Molter, Hugues Bersini, Ann Nowé, David Y. Weiss Solís:
inSilicoDb: an R/Bioconductor package for accessing human Affymetrix expert-curated datasets from GEO. Bioinform. 27(22): 3204-3205 (2011) - [j21]Yunierkis Pérez-Castillo, Matheus Froeyen, Miguel Ángel Cabrera-Pérez, Ann Nowé:
Molecular dynamics and docking simulations as a proof of high flexibility in E. coli FabH and its relevance for accurate inhibitor modeling. J. Comput. Aided Mol. Des. 25(4): 371-393 (2011) - [j20]Adelbert Groebbens, Didier Colle, Sophie De Maesschalck, Bart Puype, Kris Steenhaut, Mario Pickavet, Ann Nowé, Piet Demeester:
Logical topology design for IP rerouting: ASONs versus static OTNs. Photonic Netw. Commun. 21(2): 170-191 (2011) - [j19]Walter Colitti, Kris Steenhaut, Didier Colle, Mario Pickavet, Jan Lemeire, Ann Nowé:
Integrated routing in GMPLS-based IP/WDM networks. Photonic Netw. Commun. 21(3): 238-252 (2011) - 2010
- [j18]Sven Van Segbroeck, Steven de Jong, Ann Nowé, Francisco C. Santos, Tom Lenaerts:
Learning to coordinate in complex networks. Adapt. Behav. 18(5): 416-427 (2010) - [j17]Yann-Michaël De Hauwere, Peter Vrancx, Ann Nowé:
Generalized learning automata for multi-agent reinforcement learning. AI Commun. 23(4): 311-324 (2010) - [j16]Walter Colitti, Kris Steenhaut, Pasquale Gurzi, Ann Nowé, Didier Colle, Bart Puype, Mario Pickavet:
Service differentiation in IP/MPLS over ASON/GMPLS networks. Photonic Netw. Commun. 19(3): 301-310 (2010) - [j15]Peter Vrancx, Katja Verbeeck, Ann Nowé:
Analyzing the dynamics of stigmergetic interactions through pheromone games. Theor. Comput. Sci. 411(21): 2116-2126 (2010) - 2009
- [j14]Jonatan Taminau, Stijn Meganck, David Y. Weiss Solís, Wilma van Staveren, Geneviève Dom, David Venet, Hugues Bersini, Vincent Detours, Ann Nowé:
Validation of Merging Techniques for Cancer Microarray Data Sets. Aust. J. Intell. Inf. Process. Syst. 10(4) (2009) - [j13]Sven Van Segbroeck, Ann Nowé, Tom Lenaerts:
Stochastic Simulation of the Chemoton. Artif. Life 15(2): 213-226 (2009) - 2008
- [j12]Dimitri Staessens, Didier Colle, Ilse Lievens, Mario Pickavet, Piet Demeester, Walter Colitti, Ann Nowé, Kris Steenhaut, Ricardo Romeral:
Enabling high availability over multiple optical networks. IEEE Commun. Mag. 46(6): 120-126 (2008) - [j11]Yudel Gómez, Rafael Bello, Amilkar Puris, María M. García, Ann Nowé:
Two Step Swarm Intelligence to Solve the Feature Selection Problem. J. Univers. Comput. Sci. 14(15): 2582-2596 (2008) - [j10]Peter Vrancx, Katja Verbeeck, Ann Nowé:
Decentralized Learning in Markov Games. IEEE Trans. Syst. Man Cybern. Part B 38(4): 976-981 (2008) - 2007
- [j9]Katja Verbeeck, Ann Nowé, Johan Parent, Karl Tuyls:
Exploring selfish reinforcement learning in repeated games with stochastic rewards. Auton. Agents Multi Agent Syst. 14(3): 239-269 (2007) - 2005
- [j8]Karl Tuyls, Ann Nowé:
Evolutionary game theory and multi-agent reinforcement learning. Knowl. Eng. Rev. 20(1): 63-90 (2005) - 2004
- [j7]Johan Parent, Katja Verbeeck, Jan Lemeire, Ann Nowé, Kris Steenhaut, Erik F. Dirkx:
Adaptive load balancing of parallel applications with multi-agent reinforcement learning on heterogeneous systems. Sci. Program. 12(2): 71-79 (2004) - [j6]Karl Tuyls, Ann Nowé, Tom Lenaerts, Bernard Manderick:
An Evolutionary Game Theoretic Perspective on Learning in Multi-Agent Systems. Synth. 139(2): 297-330 (2004) - 2003
- [j5]Adelbert Groebbens, Didier Colle, Sophie De Maesschalck, Ilse Lievens, Mario Pickavet, Piet Demeester, Lan Tran, Kris Steenhaut, Ann Nowé:
Efficient Protection in MPλS Networks Using Backup Trees: Part One - Concepts and Heuristics. Photonic Netw. Commun. 6(3): 191-206 (2003) - [j4]Adelbert Groebbens, Didier Colle, Sophie De Maesschalck, Ilse Lievens, Mario Pickavet, Piet Demeester, Lan Tran, Kris Steenhaut, Ann Nowé:
Efficient Protection in MPλS Networks Using Backup Trees: Part Two - Simulations. Photonic Netw. Commun. 6(3): 207-222 (2003) - 2002
- [j3]Katja Verbeeck, Ann Nowé:
Colonies of learning automata. IEEE Trans. Syst. Man Cybern. Part B 32(6): 772-780 (2002) - 1998
- [j2]Ann Nowé:
Sugeno, Mamdani, and fuzzy Mamdani controllers put in a uniform interpolation framework. Int. J. Intell. Syst. 13(2-3): 243-256 (1998) - 1992
- [j1]Ann Nowé:
A self-tuning robust fuzzy controller. Microprocess. Microprogramming 35(1-5): 719-726 (1992)
Conference and Workshop Papers
- 2024
- [c203]Ann Nowé:
Trustworthy Reinforcement Learning: Opportunities and Challenges. AAMAS 2024: 1 - [c202]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: 1611-1620 - [c201]Alexandra Cimpean, Catholijn M. Jonker, Pieter Libin, Ann Nowé:
A Reinforcement Learning Framework for Studying Group and Individual Fairness. AAMAS 2024: 2216-2218 - [c200]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 - 2023
- [c199]Willem Röpke, Carla Groenland, Roxana Radulescu, Ann Nowé, Diederik M. Roijers:
Bridging the Gap Between Single and Multi Objective Games. AAMAS 2023: 224-232 - [c198]Willem Röpke, Diederik M. Roijers, Ann Nowé, Roxana Radulescu:
A Study of Nash Equilibria in Multi-Objective Normal-Form Games. AAMAS 2023: 269-271 - [c197]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: 1988-1990 - [c196]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: 2003-2012 - [c195]Florent Delgrange, Ann Nowé, Guillermo A. Pérez:
Wasserstein Auto-encoded MDPs: Formal Verification of Efficiently Distilled RL Policies with Many-sided Guarantees. ICLR 2023 - [c194]Axel Abels, Tom Lenaerts, Vito Trianni, Ann Nowé:
Expertise Trees Resolve Knowledge Limitations in Collective Decision-Making. ICML 2023: 79-90 - [c193]Willem Röpke, Conor F. Hayes, Patrick Mannion, Enda Howley, Ann Nowé, Diederik M. Roijers:
Distributional Multi-Objective Decision Making. IJCAI 2023: 5711-5719 - [c192]Lucas Nunes Alegre, Ana L. C. Bazzan, Ann Nowé, Bruno C. da Silva:
Multi-Step Generalized Policy Improvement by Leveraging Approximate Models. NeurIPS 2023 - [c191]Florian Felten, Lucas N. Alegre, Ann Nowé, Ana L. C. Bazzan, El-Ghazali Talbi, Grégoire Danoy, Bruno C. da Silva:
A Toolkit for Reliable Benchmarking and Research in Multi-Objective Reinforcement Learning. NeurIPS 2023 - 2022
- [c190]Florent Delgrange, Ann Nowé, Guillermo A. Pérez:
Distillation of RL Policies with Formal Guarantees via Variational Abstraction of Markov Decision Processes. AAAI 2022: 6497-6505 - [c189]Mathieu Reymond, Eugenio Bargiacchi, Ann Nowé:
Pareto Conditioned Networks. AAMAS 2022: 1110-1118 - [c188]Raphaël Avalos, Mathieu Reymond, Ann Nowé, Diederik M. Roijers:
Local Advantage Networks for Cooperative Multi-Agent Reinforcement Learning. AAMAS 2022: 1524-1526 - [c187]Jeroen Willems, Kerem Eryilmaz, Denis Steckelmacher, Bruno Depraetere, Rian Beck, Abdellatif Bey-Temsamani, Jan Helsen, Ann Nowé:
Fast Initialization of Control Parameters using Supervised Learning on Data from Similar Assets. CCTA 2022: 1214-1221 - [c186]Nixon K. Ronoh, Edna Milgo, Ambrose K. Kiprop, Bernard Manderick, Ann Nowé:
Natural gradient evolution strategies for adaptive sampling. GECCO Companion 2022: 73-74 - 2021
- [c185]Gaoyuan Liu, Joris De Winter, Bram Vanderborght, Ann Nowé, Denis Steckelmacher:
MoveRL: To a Safer Robotic Reinforcement Learning Environment. BNAIC/BENELEARN 2021: 239-253 - 2020
- [c184]Gabriel de Oliveira Ramos, Roxana Radulescu, Ann Nowé, Anderson R. Tavares:
Toll-Based Learning for Minimising Congestion under Heterogeneous Preferences. AAMAS 2020: 1098-1106 - [c183]Timothy Verstraeten, Eugenio Bargiacchi, Pieter J. K. Libin, Diederik M. Roijers, Ann Nowé:
Thompson Sampling for Factored Multi-Agent Bandits. AAMAS 2020: 2029-2031 - [c182]Yijie Zhang, Roxana Radulescu, Patrick Mannion, Diederik M. Roijers, Ann Nowé:
Opponent Modelling for Reinforcement Learning in Multi-Objective Normal Form Games. AAMAS 2020: 2080-2082 - [c181]Roxana Radulescu, Patrick Mannion, Diederik M. Roijers, Ann Nowé:
Multi-Objective Multi-Agent Decision Making: A Utility-based Analysis and Survey. AAMAS 2020: 2158-2160 - [c180]Timothy Verstraeten, Pieter J. K. Libin, Ann Nowé:
Fleet Control Using Coregionalized Gaussian Process Policy Iteration. ECAI 2020: 1571-1578 - [c179]Isel Grau, Dipankar Sengupta, María Matilde García Lorenzo, Ann Nowé:
An Interpretable Semi-supervised Classifier using Rough Sets for Amended Self-labeling. FUZZ-IEEE 2020: 1-8 - [c178]Axel Abels, Tom Lenaerts, Vito Trianni, Ann Nowé:
Collective Decision-Making as a Contextual Multi-armed Bandit Problem. ICCCI 2020: 113-124 - [c177]Axel Abels, Tom Lenaerts, Vito Trianni, Ann Nowé:
How Expert Confidence Can Improve Collective Decision-Making in Contextual Multi-Armed Bandit Problems. ICCCI 2020: 125-138 - [c176]Yailen Martínez Jiménez, Jessica Coto Palacio, Ann Nowé:
Multi-Agent Reinforcement Learning Tool for Job Shop Scheduling Problems. OLA 2020: 3-12 - [c175]Pieter J. K. Libin, Arno Moonens, Timothy Verstraeten, Fabian Perez-Sanjines, Niel Hens, Philippe Lemey, Ann Nowé:
Deep Reinforcement Learning for Large-Scale Epidemic Control. ECML/PKDD (5) 2020: 155-170 - [c174]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: 463-478 - [c173]Youri Coppens, Denis Steckelmacher, Catholijn M. Jonker, Ann Nowé:
Synthesising Reinforcement Learning Policies Through Set-Valued Inductive Rule Learning. TAILOR 2020: 163-179 - 2019
- [c172]Youri Coppens, Eugenio Bargiacchi, Ann Nowé:
A Virtual Maze Game to Explain Reinforcement Learning. BNAIC/BENELEARN 2019 - [c171]Jannick Hemelhof, Mihail Mihaylov, Ann Nowé:
Improving Zero-Intelligence Plus for Call Markets. BNAIC/BENELEARN 2019 - [c170]Pieter Libin, Nassim Versbraegen, Ana B. Abecasis, Perpetua Gomes, Tom Lenaerts, Ann Nowé:
Towards a Phylogenetic Measure to Quantify HIV Incidence. BNAIC/BENELEARN 2019 - [c169]Pieter Libin, Nassim Versbraegen, Ana B. Abecasis, Perpetua Gomes, Tom Lenaerts, Ann Nowé:
Towards a Phylogenetic Measure to Quantify HIV Incidence. BNAIC/BENELEARN (Selected Papers) 2019: 34-50 - [c168]Pieter Libin, Timothy Verstraeten, Diederik M. Roijers, Wenjia Wang, Kristof Theys, Ann Nowé:
Thompson Sampling for m-top Exploration. BNAIC/BENELEARN 2019 - [c167]Regis Loeb, Timothy Verstraeten, Ann Nowé, Ann Dooms:
Privacy Preserving Reinforcement Learning over Distributed Datasets. BNAIC/BENELEARN 2019 - [c166]Jessica Coto Palacio, Yailen Martínez Jiménez, Ann Nowé:
Multi-Agent Reinforcement Learning Tool for Job Shop Scheduling Problems. BNAIC/BENELEARN 2019 - [c165]Hélène Plisnier, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé:
Transfer Reinforcement Learning across Environment Dynamics with Multiple Advisors. BNAIC/BENELEARN 2019 - [c164]Oliver Roesler, Ann Nowé:
Action Learning and Grounding in Simulated Human-Robot Interactions. BNAIC/BENELEARN 2019 - [c163]Willem Röpke, Roxana Radulescu, Kyriakos Efthymiadis, Ann Nowé:
Training a Speech-to-Text Model for Dutch on the Corpus Gesproken Nederlands. BNAIC/BENELEARN 2019 - [c162]Willem Röpke, Roxana Radulescu, Kyriakos Efthymiadis, Ann Nowé:
DuStt - A Speech-to-Text Engine for Dutch. BNAIC/BENELEARN 2019 - [c161]Denis Steckelmacher, Hélène Plisnier, Ann Nowé:
A Motorized Wheelchair that Learns to Make its Way through a Crowd. BNAIC/BENELEARN 2019 - [c160]Denis Steckelmacher, Hélène Plisnier, Diederik M. Roijers, Ann Nowé:
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics. BNAIC/BENELEARN 2019 - [c159]Timothy Verstraeten, Ann Nowé, Jan Helsen:
Failure Avoidance for Wind Turbines through Fleetwide Control. BNAIC/BENELEARN 2019 - [c158]Felipe Gomez Marulanda, Pieter Libin, Timothy Verstraeten, Ann Nowé:
Deep hybrid approach for 3D plane segmentation. ESANN 2019 - [c157]Beatriz M. Méndez-Hernández, Erick D. Rodríguez Bazan, Yailen Martínez Jiménez, Pieter Libin, Ann Nowé:
A Multi-objective Reinforcement Learning Algorithm for JSSP. ICANN (1) 2019: 567-584 - [c156]Axel Abels, Diederik M. Roijers, Tom Lenaerts, Ann Nowé, Denis Steckelmacher:
Dynamic Weights in Multi-Objective Deep Reinforcement Learning. ICML 2019: 11-20 - [c155]Anna Harutyunyan, Peter Vrancx, Philippe Hamel, Ann Nowé, Doina Precup:
Per-Decision Option Discounting. ICML 2019: 2644-2652 - [c154]Pieter Libin, Timothy Verstraeten, Diederik M. Roijers, Wenjia Wang, Kristof Theys, Ann Nowé:
Bayesian Anytime m-top Exploration. ICTAI 2019: 1422-1428 - [c153]Richar Sosa, Alejandro Alfonso, Gonzalo Nápoles, Rafael Bello, Koen Vanhoof, Ann Nowé:
Synaptic Learning of Long-Term Cognitive Networks with Inputs. IJCNN 2019: 1-8 - [c152]Denis Steckelmacher, Hélène Plisnier, Diederik M. Roijers, Ann Nowé:
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics. ECML/PKDD (3) 2019: 19-34 - [c151]Angel Luis Scull Pupo, Jens Nicolay, Kyriakos Efthymiadis, Ann Nowé, Coen De Roover, Elisa Gonzalez Boix:
GUARDIAML: Machine Learning-Assisted Dynamic Information Flow Control. SANER 2019: 624-628 - 2018
- [c150]Anna Harutyunyan, Peter Vrancx, Pierre-Luc Bacon, Doina Precup, Ann Nowé:
Learning With Options That Terminate Off-Policy. AAAI 2018: 3173-3182 - [c149]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: 4099-4106 - [c148]Dennis J. N. J. Soemers, Tim Brys, Kurt Driessens, Mark H. M. Winands, Ann Nowé:
Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees. AAAI 2018: 7831-7836 - [c147]Lázaro Lugo, Marilyn Bello, Ann Nowé, Rafael Bello:
A Solution for the Team Selection Problem Using ACO. ANTS Conference 2018: 325-332 - [c146]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: 1477-1485 - [c145]Roxana Radulescu, Manon Legrand, Kyriakos Efthymiadis, Diederik M. Roijers, Ann Nowé:
Deep Multi-agent Reinforcement Learning in a Homogeneous Open Population. BNCAI 2018: 90-105 - [c144]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: 491-499 - [c143]Felipe Gomez Marulanda, Pieter Libin, Timothy Verstraeten, Ann Nowé:
IPC-Net: 3D Point-Cloud Segmentation Using Deep Inter-Point Convolutional Layers. ICTAI 2018: 293-301 - [c142]Beatriz M. Méndez-Hernández, Jessica Coto Palacio, Yailen Martínez Jiménez, Ann Nowé, Erick D. Rodríguez Bazan:
A Reinforcement Learning Approach for the Report Scheduling Process Under Multiple Constraints. IWAIPR 2018: 228-235 - [c141]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: 456-471 - [c140]Christophe Patyn, Thijs Peirelinck, Geert Deconinck, Ann Nowé:
Intelligent Electric Water Heater Control with Varying State Information. SmartGridComm 2018: 1-6 - 2017
- [c139]Elias Fernández Domingos, Juan-Carlos Burguillo, Ann Nowé, Tom Lenaerts:
Coordinating Human and Agent Behavior in Collective-Risk Scenarios. AAAI 2017: 4919-4920 - [c138]Diederik M. Roijers, Luisa M. Zintgraf, Ann Nowé:
Interactive Thompson Sampling for Multi-objective Multi-armed Bandits. ADT 2017: 18-34 - [c137]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: 67-85 - [c136]Roxana Radulescu, Peter Vrancx, Ann Nowé:
Analysing Congestion Problems in Multi-agent Reinforcement Learning. AAMAS 2017: 1705-1707 - [c135]Leticia Arco, Gladys Casas, Ann Nowé:
Clustering methodology for smart metering data based on local and global features. IML 2017: 65:1-65:13 - [c134]Steven Adriaensen, Filip Moons, Ann Nowé:
An Importance Sampling Approach to the Estimation of Algorithm Performance in Automated Algorithm Design. LION 2017: 3-17 - 2016
- [c133]Vitalio Alfonso Reguera, Erik Ortiz Guerra, Carlos Manuel García Algora, Ann Nowé, Kris Steenhaut:
On the upper bound for the time to rendezvous in multi-hop cognitive radio networks. CAMAD 2016: 31-36 - [c132]Steven Adriaensen, Ann Nowé:
Case study: An analysis of accidental complexity in a state-of-the-art hyper-heuristic for HyFlex. CEC 2016: 1485-1492 - [c131]Sofie De Clercq, Steven Schockaert, Ann Nowé, Martine De Cock:
Formalizing Commitment-Based Deals in Boolean Games. ECAI 2016: 329-337 - [c130]Ewelina Swiderska, Jakub Lasisz, Aleksander Byrski, Tom Lenaerts, Dana Samson, Bipin Indurkhya, Ann Nowé, Marek Kisiel-Dorohinicki:
Measuring Diversity of Socio-Cognitively Inspired ACO Search. EvoApplications (1) 2016: 393-408 - [c129]Iwan Bugajski, Piotr Listkiewicz, Aleksander Byrski, Marek Kisiel-Dorohinicki, Wojciech Korczynski, Tom Lenaerts, Dana Samson, Bipin Indurkhya, Ann Nowé:
Enhancing Particle Swarm Optimization with Socio-cognitive Inspirations. ICCS 2016: 804-813 - [c128]Steven Adriaensen, Ann Nowé:
Towards a White Box Approach to Automated Algorithm Design. IJCAI 2016: 554-560 - [c127]Dewan Md. Farid, Ann Nowé, Bernard Manderick:
Ensemble of Trees for Classifying High-Dimensional Imbalanced Genomic Data. IntelliSys (1) 2016: 172-187 - [c126]Isel Grau, Dipankar Sengupta, Dewan Md. Farid, Bernard Manderick, Ann Nowé, María Matilde García Lorenzo, Dorien Daneels, Maryse Bonduelle, Didier Croes, Sonia Van Dooren:
Genomic Variant Classifier Tool. IntelliSys (1) 2016: 453-456 - [c125]Andres Auquilla, Yannick De Bock, Ann Nowé, Joost R. Duflou:
Combining Occupancy User Profiles in a Multi-user Environment: An Academic Office Case Study. Intelligent Environments 2016: 186-189 - [c124]Mihail Mihaylov, Iván S. Razo-Zapata, Roxana Radulescu, Sergio Jurado, Narcís Avellana, Ann Nowé:
Smart Grid Demonstration Platform for Renewable Energy Exchange. PAAMS 2016: 277-280 - [c123]Carlos Manuel García Algora, Ernesto Prieto Lopez, Vitalio Alfonso Reguera, Ann Nowé, Kris Steenhaut:
Poster: Comparative study of EM-MAC and TSCH/orchestra for IoT. SCVT 2016: 1-6 - [c122]Iván S. Razo-Zapata, Mihail Mihaylov, Ann Nowé:
Analysing the Impact of Storage and Load Shifting on Grey Energy Demand Reduction. SMARTGREENS/VEHITS (Selected Papers) 2016: 27-48 - [c121]Iván S. Razo-Zapata, Mihail Mihaylov, Ann Nowé:
Integration of Load Shifting and Storage to Reduce Gray Energy Demand. SMARTGREENS 2016: 154-165 - [c120]Ann Nowé, Tim Brys:
A Gentle Introduction to Reinforcement Learning. SUM 2016: 18-32 - 2015
- [c119]Anna Harutyunyan, Sam Devlin, Peter Vrancx, Ann Nowé:
Expressing Arbitrary Reward Functions as Potential-Based Advice. AAAI 2015: 2652-2658 - [c118]Tim Brys, Anna Harutyunyan, Matthew E. Taylor, Ann Nowé:
Policy Transfer using Reward Shaping. AAMAS 2015: 181-188 - [c117]Anna Harutyunyan, Tim Brys, Peter Vrancx, Ann Nowé:
Multi-Scale Reward Shaping via an Off-Policy Ensemble. AAMAS 2015: 1641-1642 - [c116]Anna Harutyunyan, Tim Brys, Peter Vrancx, Ann Nowé:
Shaping Mario with Human Advice. AAMAS 2015: 1913-1914 - [c115]Mihail Mihaylov, Sergio Jurado, Narcís Avellana, Iván S. Razo-Zapata, Kristof Van Moffaert, Leticia Arco, Maite Bezunartea, Isel Grau, Adrian Cañadas, Ann Nowé:
SCANERGY: a Scalable and Modular System for Energy Trading Between Prosumers. AAMAS 2015: 1917-1918 - [c114]Steven Adriaensen, Gabriela Ochoa, Ann Nowé:
A benchmark set extension and comparative study for the HyFlex framework. CEC 2015: 784-791 - [c113]Kristof Van Moffaert, Tim Brys, Ann Nowé:
Risk-sensitivity through multi-objective reinforcement learning. CEC 2015: 1746-1753 - [c112]S. Rodrigues, Rodrigo Teixeira Pinto, Pavol Bauer, Tim Brys, Ann Nowé:
Online Distributed Voltage Control of an offshore MTdc network using reinforcement learning. CEC 2015: 1769-1775 - [c111]Sofie De Clercq, Steven Schockaert, Ann Nowé, Martine De Cock:
Multilateral Negotiation in Boolean Games with Incomplete Information Using Generalized Possibilistic Logic. IJCAI 2015: 2890-2896 - [c110]Tim Brys, Anna Harutyunyan, Halit Bener Suay, Sonia Chernova, Matthew E. Taylor, Ann Nowé:
Reinforcement Learning from Demonstration through Shaping. IJCAI 2015: 3352-3358 - [c109]Ivomar Brito Soares, Yann-Michaël De Hauwere, Kris Januarius, Tim Brys, Thierry Salvant, Ann Nowé:
Departure MANagement with a Reinforcement Learning Approach: Respecting CFMU Slots. ITSC 2015: 1169-1176 - [c108]Kevin Van Vaerenbergh, Yann-Michaël De Hauwere, Bruno Depraetere, Kristof Van Moffaert, Ann Nowé:
A Policy Gradient with Parameter-Based Exploration Approach for Zone-Heating. SSCI 2015: 556-563 - 2014
- [c107]Tim Brys, Ann Nowé, Daniel Kudenko, Matthew E. Taylor:
Combining Multiple Correlated Reward and Shaping Signals by Measuring Confidence. AAAI 2014: 1687-1693 - [c106]Tim Brys, Ann Nowé:
Reinforcement Learning on Multiple Correlated Signals. AAAI 2014: 3065-3066 - [c105]Madalina M. Drugan, Ann Nowé, Bernard Manderick:
Pareto Upper Confidence Bounds algorithms: An empirical study. ADPRL 2014: 1-8 - [c104]Tim Brys, Kristof Van Moffaert, Ann Nowé, Matthew E. Taylor:
Adaptive objective selection for correlated objectives in multi-objective reinforcement learning. AAMAS 2014: 1349-1350 - [c103]Steven Adriaensen, Tim Brys, Ann Nowé:
Designing reusable metaheuristic methods: A semi-automated approach. IEEE Congress on Evolutionary Computation 2014: 2969-2976 - [c102]Tim Brys, Matthew E. Taylor, Ann Nowé:
Using Ensemble Techniques and Multi-Objectivization to Solve Reinforcement Learning Problems. ECAI 2014: 981-982 - [c101]Anna Harutyunyan, Tim Brys, Peter Vrancx, Ann Nowé:
Off-Policy Shaping Ensembles in Reinforcement Learning. ECAI 2014: 1021-1022 - [c100]Ildefons Magrans de Abril, Ann Nowé:
Supervised Neural Network Structure Recovery. Neural Connectomics 2014: 35-41 - [c99]Steven Adriaensen, Tim Brys, Ann Nowé:
Fair-share ILS: a simple state-of-the-art iterated local search hyperheuristic. GECCO 2014: 1303-1310 - [c98]Sofie De Clercq, Kim Bauters, Steven Schockaert, Mihail Mihaylov, Martine De Cock, Ann Nowé:
Decentralized Computation of Pareto Optimal Pure Nash Equilibria of Boolean Games with Privacy Concerns . ICAART (2) 2014: 50-59 - [c97]Kristof Van Moffaert, Tim Brys, Arjun Chandra, Lukas Esterle, Peter R. Lewis, Ann Nowé:
A novel adaptive weight selection algorithm for multi-objective multi-agent reinforcement learning. IJCNN 2014: 2306-2314 - [c96]Tim Brys, Anna Harutyunyan, Peter Vrancx, Matthew E. Taylor, Daniel Kudenko, Ann Nowé:
Multi-objectivization of reinforcement learning problems by reward shaping. IJCNN 2014: 2315-2322 - [c95]Kristof Van Moffaert, Kevin Van Vaerenbergh, Peter Vrancx, Ann Nowé:
Multi-objective χ-Armed bandits. IJCNN 2014: 2331-2338 - [c94]Madalina M. Drugan, Ann Nowé:
Scalarization based Pareto optimal set of arms identification algorithms. IJCNN 2014: 2690-2697 - [c93]Sofie De Clercq, Steven Schockaert, Martine De Cock, Ann Nowé:
Possibilistic Boolean Games: Strategic Reasoning under Incomplete Information. JELIA 2014: 196-209 - [c92]Sofie De Clercq, Kim Bauters, Steven Schockaert, Martine De Cock, Ann Nowé:
Using Answer Set Programming for Solving Boolean Games. KR 2014 - [c91]Mihail Mihaylov, Sergio Jurado, Kristof Van Moffaert, Narcís Avellana, Ann Nowé:
NRG-X-Change - A Novel Mechanism for Trading of Renewable Energy in Smart Grids. SMARTGREENS 2014: 101-106 - 2013
- [c90]Kristof Van Moffaert, Madalina M. Drugan, Ann Nowé:
Scalarized multi-objective reinforcement learning: Novel design techniques. ADPRL 2013: 191-199 - [c89]Abdel Rodríguez, Peter Vrancx, Ann Nowé, Erik Hostens:
Model-free learning of wire winding control. ASCC 2013: 1-6 - [c88]Tim Brys, Madalina M. Drugan, Ann Nowé:
Meta-Evolutionary Algorithms and recombination operators for satisfiability solving in fuzzy logics. IEEE Congress on Evolutionary Computation 2013: 1060-1067 - [c87]Kristof Van Moffaert, Madalina M. Drugan, Ann Nowé:
Hypervolume-Based Multi-Objective Reinforcement Learning. EMO 2013: 352-366 - [c86]Tim Brys, Madalina M. Drugan, Peter A. N. Bosman, Martine De Cock, Ann Nowé:
Solving satisfiability in fuzzy logics by mixing CMA-ES. GECCO 2013: 1125-1132 - [c85]Tim Brys, Madalina M. Drugan, Peter A. N. Bosman, Martine De Cock, Ann Nowé:
Local search and restart strategies for satisfiability solving in fuzzy logics. GEFS 2013: 52-59 - [c84]Kristof Van Moffaert, Yann-Michaël De Hauwere, Peter Vrancx, Ann Nowé:
Reinforcement Learning for Multi-purpose Schedules. ICAART (2) 2013: 203-209 - [c83]Tim Brys, Kristof Van Moffaert, Kevin Van Vaerenbergh, Ann Nowé:
On the Behaviour of Scalarization Methods for the Engagement of a Wet Clutch. ICMLA (1) 2013: 258-263 - [c82]Madalina M. Drugan, Ann Nowé:
Designing multi-objective multi-armed bandits algorithms: A study. IJCNN 2013: 1-8 - [c81]Yann-Michaël De Hauwere, Kristof Van Moffaert, Paul-Armand Verhaegen, Ann Nowé:
Networks as a tool to save energy while keeping up general user comfort in buildings. LANMAN 2013: 1-6 - [c80]Sofie De Clercq, Steven Schockaert, Martine De Cock, Ann Nowé:
Modeling Stable Matching Problems with Answer Set Programming. RuleML 2013: 68-83 - 2012
- [c79]Tim Brys, Ann Nowé:
Improving Convergence of CMA-ES Through Structure-Driven Discrete Recombination. AAAI 2012: 2415-2416 - [c78]Yann-Michaël De Hauwere, Ann Nowé:
Learning Conflicts from Experience. MAPF@AAAI 2012 - [c77]Abdel Rodríguez, Peter Vrancx, Ricardo Grau Ábalo, Ann Nowé:
An RL approach to common-interest continuous action games. AAMAS 2012: 1401-1402 - [c76]Wajdi Halabi, Kris Steenhaut, Marnix Goossens, Ann Nowé:
Cross layer routing in optical IP/WDM multi-domain networks. ICUMT 2012: 607-612 - [c75]Cosmin Lazar, Luca Demarchi, David Steenhoff, Jonathan Cheung-Wai Chan, Ann Nowé, Hichem Sahli:
Local linear spectral unmixing via cluster analysis and non-negative matrix factorization for hyperspectral (CHRIS/PROBA) imagery. IGARSS 2012: 7267-7270 - [c74]Kevin Van Vaerenbergh, Abdel Rodríguez, Matteo Gagliolo, Peter Vrancx, Ann Nowé, Julian Stoev, Stijn Goossens, Gregory Pinte, Wim Symens:
Improving wet clutch engagement with reinforcement learning. IJCNN 2012: 1-8 - [c73]Wolney Leal De Mello Neto, Ann Nowé:
Insights on Social Recommender Systems. RUE@RecSys 2012: 33-38 - [c72]Bart Lemmens, Kris Steenhaut, Peter Ruckebusch, Ingrid Moerman, Ann Nowé:
Network-wide synchronization in Wireless Sensor Networks. SCVT 2012: 1-5 - 2011
- [c71]Yann-Michaël De Hauwere, Peter Vrancx, Ann Nowé:
Solving Sparse Delayed Coordination Problems in Multi-Agent Reinforcement Learning. ALA 2011: 114-133 - [c70]Mihail Mihaylov, Yann-Aël Le Borgne, Karl Tuyls, Ann Nowé:
Distributed cooperation in wireless sensor networks. AAMAS 2011: 249-256 - [c69]Yann-Michaël De Hauwere, Peter Vrancx, Ann Nowé:
Solving delayed coordination problems in MAS. AAMAS 2011: 1115-1116 - [c68]Tim Brys, Yann-Michaël De Hauwere, Ann Nowé, Peter Vrancx:
Local Coordination in Online Distributed Constraint Optimization Problems. EUMAS 2011: 31-47 - [c67]Mihail Mihaylov, Yann-Aël Le Borgne, Ann Nowé, Karl Tuyls:
Self-organizing Synchronicity and Desynchronicity using Reinforcement Learning. ICAART (2) 2011: 94-103 - [c66]Yann-Michaël De Hauwere, Peter Vrancx, Ann Nowé:
Adaptive State Representations for Multi-agent Reinforcement Learning. ICAART (2) 2011: 181-189 - [c65]Peter Vrancx, Yann-Michaël De Hauwere, Ann Nowé:
Transfer Learning for Multi-agent Coordination. ICAART (2) 2011: 263-272 - [c64]Mihail Mihaylov, Yann-Aël Le Borgne, Karl Tuyls, Ann Nowé:
Reinforcement Learning for Self-organizing Wake-Up Scheduling in Wireless Sensor Networks. ICAART (Revised Selected Papers) 2011: 382-396 - [c63]Abdel Rodríguez, Ricardo Grau Ábalo, Ann Nowé:
Continuous Action Reinforcement Learning Automata - Performance and Convergence. ICAART (2) 2011: 473-478 - [c62]Wajdi Halabi, Kris Steenhaut, Marnix Goossens, Ann Nowé:
Routing and traffic grooming in multi-domain optical networks. ICUMT 2011: 1-7 - [c61]Pasquale Gurzi, Kris Steenhaut, Ann Nowé, Peter Vrancx:
Learning a pricing strategy in multi-domain DWDM networks. LANMAN 2011: 1-6 - [c60]Yailen Martínez, Ann Nowé, Juliett Suárez, Rafael Bello:
A Reinforcement Learning Approach for the Flexible Job Shop Scheduling Problem. LION 2011: 253-262 - [c59]Nashat Abughalieh, Kris Steenhaut, Bart Lemmens, Ann Nowé:
Parallel Concatenation vs. Serial Concatenation Turbo Codes for Wireless Sensor Networks. SCVT 2011: 1-6 - [c58]Wajdi Halabi, Kris Steenhaut, Ann Nowé, Pasquale Gurzi:
Routing and signaling in GMPLS based DWDM multi domain multilayer networks using IP/WDM router. WOCN 2011: 1-5 - 2010
- [c57]Yann-Michaël De Hauwere, Peter Vrancx, Ann Nowé:
Learning multi-agent state space representations. AAMAS 2010: 715-722 - [c56]Peter Vrancx, Katja Verbeeck, Ann Nowé:
Taking turns in general sum Markov games. AAMAS 2010: 1439-1440 - [c55]Jonatan Taminau, Stijn Meganck, Cosmin Lazar, David Y. Weiss Solís, Alain Coletta, Nic Walker, Hugues Bersini, Ann Nowé:
Sequential Application of Feature Selection and Extraction for Predicting Breast Cancer Aggressiveness. CSBio 2010: 46-57 - [c54]Cosmin Lazar, Danielle Nuzillard, Ann Nowé:
A New Geometrical BSS Approach for Non Negative Sources. LVA/ICA 2010: 530-537 - [c53]Nashat Abughalieh, Yann-Aël Le Borgne, Ann Nowé, Kris Steenhaut:
Lifetime optimization for sensor networks with correlated data gathering. INSS 2010: 69-72 - [c52]Yann-Aël Le Borgne, Ann Nowé, Nashat Abughalieh, Kris Steenhaut:
Distributed regression for high-level feature extraction in wireless sensor networks. INSS 2010: 249-252 - [c51]Yann-Aël Le Borgne, Ann Nowé, Kris Steenhaut, Gianluca Bontempi:
Demonstrating principal component aggregation for distributed spatial pattern recognition. IPSN 2010: 430-431 - [c50]Nashat Abughalieh, Yann-Aël Le Borgne, Kris Steenhaut, Ann Nowé:
Lifetime optimization for wireless sensor networks with correlated data gathering. WiOpt 2010: 266-272 - 2009
- [c49]Mihail Mihaylov, Karl Tuyls, Ann Nowé:
Decentralized Learning in Wireless Sensor Networks. ALA 2009: 60-73 - [c48]Sven Van Segbroeck, Francisco C. Santos, Ann Nowé, Jorge M. Pacheco, Tom Lenaerts:
The coevolution of loyalty and cooperation. IEEE Congress on Evolutionary Computation 2009: 500-505 - [c47]Joris Borms, Kris Steenhaut, Bart Lemmens, Ann Nowé:
Power Aware Fulfilment of Latency Requirements by Exploiting Heterogeneity in Wireless Sensor and Actuator Networks. DSD 2009: 597-600 - [c46]Pasquale Gurzi, Walter Colitti, Kris Steenhaut, Ann Nowé:
Maximum flow based Routing and Wavelength Assignment in all-optical networks. ICUMT 2009: 1-6 - [c45]Yudel Gómez, Rafael Bello, Ann Nowé, Enrique Casanovas, Jonatan Taminau:
Multi-colony ACO and Rough Set Theory to Distributed Feature Selection Problem. IWANN (2) 2009: 458-461 - 2008
- [c44]Hugues Smeets, Kris Steenhaut, Ann Nowé:
An Efficient Distributed Self-Organizing Routing Algorithm for Wireless Sensor Networks. CISIS 2008: 19-25 - [c43]Walter Colitti, Kris Steenhaut, Ann Nowé:
Multilayer traffic engineering and DiffServ in the next generation internet. COMSWARE 2008: 591-598 - [c42]Walter Colitti, Pasquale Gurzi, Kris Steenhaut, Ann Nowé:
Adaptive multilayer routing in the next generation GMPLS Internet. COMSWARE 2008: 768-775 - [c41]Yudel Gómez, Rafael Bello, Ann Nowé, Frank Bosmans:
Speeding-Up ACO Implementation by Decreasing the Number of Heuristic Function Evaluations in Feature Selection Problem. IWPACBB 2008: 223-232 - [c40]Yann-Michaël De Hauwere, Peter Vrancx, Ann Nowé:
Using Generalized Learning Automata for State Space Aggregation in MAS. KES (1) 2008: 182-193 - [c39]Maarten Peeters, Ville Könönen, Katja Verbeeck, Ann Nowé:
A Learning Automata Approach to Multi-agent Policy Gradient Learning. KES (2) 2008: 379-390 - [c38]Maarten Peeters, Ville Könönen, Katja Verbeeck, Sven Van Segbroeck, Ann Nowé:
Coordinated Exploration in Conflicting Multi-stage Games. KES (2) 2008: 391-402 - [c37]Isis Bonet, Abdel Rodríguez, Ricardo Grau Ábalo, María M. García, Yvan Saeys, Ann Nowé:
Comparing Distance Measures with Visual Methods. MICAI 2008: 90-99 - 2007
- [c36]Nyree Lemmens, Steven de Jong, Karl Tuyls, Ann Nowé:
Bee Behaviour in Multi-agent Systems. Adaptive Agents and Multi-Agents Systems 2007: 145-156 - [c35]Maarten Peeters, Katja Verbeeck, Ann Nowé:
Solving Multi-stage Games with Hierarchical Learning Automata That Bootstrap. Adaptive Agents and Multi-Agents Systems 2007: 169-187 - [c34]Peter Vrancx, Katja Verbeeck, Ann Nowé:
Networks of Learning Automata and Limiting Games. Adaptive Agents and Multi-Agents Systems 2007: 224-238 - [c33]Amilkar Puris, Rafael Bello, Yaima Trujillo, Ann Nowé, Yailen Martínez:
Two-Stage ACO to Solve the Job Shop Scheduling Problem. CIARP 2007: 447-456 - [c32]Rafael Bello, Yudel Gómez, María M. García, Ann Nowé:
Two-Step Particle Swarm Optimization to Solve the Feature Selection Problem. ISDA 2007: 691-696 - [c31]Amilkar Puris, Rafael Bello, Yailen Martínez, Ann Nowé:
Two-Stage Ant Colony Optimization for Solving the Traveling Salesman Problem. IWINAC (2) 2007: 307-316 - [c30]Peter Vrancx, Katja Verbeeck, Ann Nowé:
Optimal Convergence in Multi-Agent MDPs. KES (3) 2007: 107-114 - [c29]Walter Colitti, Kris Steenhaut, Ann Nowé:
QoS in GMPLS based IP/DWDM Metro Networks. LANMAN 2007: 84-89 - [c28]Walter Colitti, Kris Steenhaut, Ann Nowé, Jan Lemeire:
Multilayer Quality and Grade of Service Support for High Speed GMPLS IP/DWDM Networks. NBiS 2007: 187-196 - 2006
- [c27]Peter Vrancx, Ann Nowé:
Using Pheromone Repulsion to Find Disjoint Paths. ANTS Workshop 2006: 522-523 - [c26]Rafael Bello, Amilkar Puris, Ann Nowé, Yailen Martínez, María M. García:
Two Step Ant Colony System to Solve the Feature Selection Problem. CIARP 2006: 588-596 - [c25]Ann Nowé, Katja Verbeeck, Maarten Peeters:
Learning Automata as a Basis for Multi Agent Reinforcement Learning. EUMAS 2006 - [c24]Ronald L. Westra, Karl Tuyls, Yvan Saeys, Ann Nowé:
Knowledge Discovery and Emergent Complexity in Bioinformatics. KDECB 2006: 1-9 - [c23]Peter Vrancx, Katja Verbeeck, Ann Nowé:
Analyzing Stigmergetic Algorithms Through Automata Games. KDECB 2006: 145-156 - [c22]Yaile Caballero, Rafael Bello, Alberto Taboada-Crispí, Ann Nowé, María M. García, Gladys Casas:
A New Measure Based in the Rough Set Theory to Estimate the Training Set Quality. SYNASC 2006: 133-140 - 2005
- [c21]Katja Verbeeck, Ann Nowé, Maarten Peeters, Karl Tuyls:
Multi-agent Reinforcement Learning in Stochastic Single and Multi-stage Games. Adaptive Agents and Multi-Agent Systems 2005: 275-294 - [c20]Katja Verbeeck, Ann Nowé, Karl Tuyls:
Coordinated exploration in multi-agent reinforcement learning: an application to load-balancing. AAMAS 2005: 1105-1106 - [c19]Johan Parent, Ann Nowé, Anne Defaweux, Kris Steenhaut:
Compressed Linear Genetic Programming: empirical parameter study on the Even-n-parity problem. BNAIC 2005: 373-374 - [c18]Johan Parent, Ann Nowé, Kris Steenhaut, Anne Defaweux:
Linear genetic programming using a compressed genotype representation. Congress on Evolutionary Computation 2005: 1164-1171 - [c17]Peter Vrancx, Ann Nowé, Kris Steenhaut:
Multi-type ACO for light path protection. EUMAS 2005: 513 - [c16]Pieter Beyens, Ann Nowé, Kris Steenhaut:
High-density wireless sensor networks: a new clustering approach for prediction-based monitoring. EWSN 2005: 188-196 - [c15]Rafael Bello, Ann Nowé, Yaile Caballero, Yudel Gómez, Peter Vrancx:
A model based on ant colony system and rough set theory to feature selection. GECCO 2005: 275-276 - [c14]Ann Nowé, Katja Verbeeck, Maarten Peeters:
Learning Automata as a Basis for Multi Agent Reinforcement Learning. LAMAS 2005: 71-85 - [c13]Peter Vrancx, Ann Nowé, Kris Steenhaut:
Multi-type ACO for Light Path Protection. LAMAS 2005: 207-215 - 2004
- [c12]Maarten Peeters, Katja Verbeeck, Ann Nowé:
Multi-Agent Learning in Conflicting Multi-Level Games with Incomplete Information. AAAI Technical Report (2) 2004: 73-80 - [c11]Ann Nowé, Katja Verbeeck, Peter Vrancx:
Multi-type Ant Colony: The Edge Disjoint Paths Problem. ANTS Workshop 2004: 202-213 - 2003
- [c10]Karl Tuyls, Dries Heytens, Ann Nowé, Bernard Manderick:
Extended Replicator Dynamics as a Key to Reinforcement Learning in Multi-agent Systems. ECML 2003: 421-431 - [c9]Lan Tran, Kris Steenhaut, Ann Nowé, Mario Pickavet, Piet Demeester:
Efficient Usage of Capacity Resources in Survivable MP lambda S Networks. QoS-IP 2003: 204-217 - 2002
- [c8]Katja Verbeeck, Ann Nowé, Tom Lenaerts, Johan Parent:
Learning to Reach the Pareto Optimal Nash Equilibrium as a Team. Australian Joint Conference on Artificial Intelligence 2002: 407-418 - [c7]Johan Parent, Ann Nowé:
Evolving Compression Preprocessors With Genetic Programming. GECCO 2002: 861-867 - [c6]Katja Verbeeck, Johan Parent, Ann Nowé:
Homo Egualis Reinforcement Learning Agents for Load Balancing. WRAC 2002: 81-91 - 2001
- [c5]Ann Nowé, Johan Parent, Katja Verbeeck:
Social Agents Playing a Periodical Policy. ECML 2001: 382-393 - 1999
- [c4]Ann Nowé, Katja Verbeeck:
Formalizing the Ant Algorithms in Terms of Reinforcement Learning. ECAL 1999: 616-620 - 1998
- [c3]Ann Nowé, Kris Steenhaut, Mohamed Fakir, Katja Verbeeck:
Q-learning for adaptive load based routing. SMC 1998: 3965-3970 - 1993
- [c2]Ann Nowé, Ranjan Vepa:
A Reinforcement Learning Algorithm based on "Safety". FLAI 1993: 47-58 - 1989
- [c1]Viviane Jonckers, Ann Nowé:
An environment for knowledge based transformational implementation. IEA/AIE (2) 1989: 610-619
Parts in Books or Collections
- 2012
- [p5]Ann Nowé, Peter Vrancx, Yann-Michaël De Hauwere:
Game Theory and Multi-agent Reinforcement Learning. Reinforcement Learning 2012: 441-470 - 2010
- [p4]Yann-Michaël De Hauwere, Peter Vrancx, Ann Nowé:
Multi-Agent Systems and Large State Spaces. Agent and Multi-agent Technology for Internet and Enterprise Systems 2010: 181-205 - 2009
- [p3]Martin Köhn, Walter Colitti, Pasquale Gurzi, Ann Nowé, Kris Steenhaut:
Multi-layer Traffic Engineering (MTE) in Grooming Enabled ASON/GMPLS Networks. COST Action 291 Final Report 2009: 237-252 - [p2]Sébastien Rumley, Christian Gaumier, Ramon Aparicio-Pardo, Ching-Hung Chang, Walter Colitti, Belen Garcia-Manrubia, Pandelis Kourtessis, Juan Antonio Martínez León, Ann Nowé, Pablo Pavón-Mariño, Joachim Scharf, Kris Steenhaut:
Software Tools and Methods for Research and Education in Optical Networks. COST Action 291 Final Report 2009: 331-364 - 2008
- [p1]Karl Tuyls, Ann Nowé:
Introduction to Game Theory. Wiley Encyclopedia of Computer Science and Engineering 2008
Editorship
- 2023
- [e6]Kobi Gal, Ann Nowé, Grzegorz J. Nalepa, Roy Fairstein, Roxana Radulescu:
ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland - Including 12th Conference on Prestigious Applications of Intelligent Systems (PAIS 2023). Frontiers in Artificial Intelligence and Applications 372, IOS Press 2023, ISBN 978-1-64368-436-9 [contents] - 2021
- [e5]Frank Dignum, Alessio Lomuscio, Ulle Endriss, Ann Nowé:
AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, Virtual Event, United Kingdom, May 3-7, 2021. ACM 2021, ISBN 978-1-4503-8307-3 [contents] - 2008
- [e4]Karl Tuyls, Ann Nowé, Zahia Guessoum, Daniel Kudenko:
Adaptive Agents and Multi-Agent Systems III. Adaptation and Multi-Agent Learning, 5th, 6th, and 7th European Symposium, ALAMAS 2005-2007 on Adaptive and Learning Agents and Multi-Agent Systems, Revised Selected Papers. Lecture Notes in Computer Science 4865, Springer 2008, ISBN 978-3-540-77947-6 [contents] - 2007
- [e3]Karl Tuyls, Ronald L. Westra, Yvan Saeys, Ann Nowé:
Knowledge Discovery and Emergent Complexity in Bioinformatics, First International Workshop, KDECB 2006, Ghent, Belgium, May 10, 2006. Revised Selected Papers. Lecture Notes in Computer Science 4366, Springer 2007, ISBN 978-3-540-71036-3 [contents] - 2005
- [e2]Katja Verbeeck, Karl Tuyls, Ann Nowé, Bernard Manderick, Bart Kuijpers:
BNAIC 2005 - Proceedings of the Seventeenth Belgium-Netherlands Conference on Artificial Intelligence, Brussels, Belgium, October 17-18, 2005. Koninklijke Vlaamse Academie van Belie voor Wetenschappen en Kunsten 2005 [contents] - [e1]Marie-Pierre Gleizes, Gal A. Kaminka, Ann Nowé, Sascha Ossowski, Karl Tuyls, Katja Verbeeck:
EUMAS 2005 - Proceedings of the Third European Workshop on Multi-Agent Systems, Brussels, Belgium, December 7-8, 2005. Koninklijke Vlaamse Academie van Belie voor Wetenschappen en Kunsten 2005 [contents]
Data and Artifacts
- 2022
- [d2]Alexandre Renaux, Ann Nowé, Tom Lenaerts:
BOCK: Biological networks and Oligogenic Combinations as a Knowledge graph. Version 1.0. Zenodo, 2022 [all versions]
- [d1]Alexandre Renaux, Ann Nowé, Tom Lenaerts:
BOCK: Biological networks and Oligogenic Combinations as a Knowledge graph. Version 1.0. Zenodo, 2022 [all versions]
Informal and Other Publications
- 2024
- [i51]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 abs/2402.07182 (2024) - [i50]Florent Delgrange, Guy Avni, Anna Lukina, Christian Schilling, Ann Nowé, Guillermo A. Pérez:
Synthesis of Hierarchical Controllers Based on Deep Reinforcement Learning Policies. CoRR abs/2402.13785 (2024) - [i49]Axel Abels, Elias Fernández Domingos, Ann Nowé, Tom Lenaerts:
Mitigating Biases in Collective Decision-Making: Enhancing Performance in the Face of Fake News. CoRR abs/2403.08829 (2024) - [i48]Yannick Molinghen, Raphaël Avalos, Mark Van Achter, Ann Nowé, Tom Lenaerts:
Laser Learning Environment: A new environment for coordination-critical multi-agent tasks. CoRR abs/2404.03596 (2024) - [i47]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 abs/2407.16312 (2024) - [i46]Raphaël Avalos, Eugenio Bargiacchi, Ann Nowé, Diederik M. Roijers, Frans A. Oliehoek:
Online Planning in POMDPs with State-Requests. CoRR abs/2407.18812 (2024) - 2023
- [i45]Willem Röpke, Carla Groenland, Roxana Radulescu, Ann Nowé, Diederik M. Roijers:
Bridging the Gap Between Single and Multi Objective Games. CoRR abs/2301.05755 (2023) - [i44]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 abs/2301.07784 (2023) - [i43]Hélène Plisnier, Denis Steckelmacher, Jeroen Willems, Bruno Depraetere, Ann Nowé:
Transferring Multiple Policies to Hotstart Reinforcement Learning in an Air Compressor Management Problem. CoRR abs/2301.12820 (2023) - [i42]Alexandra Cimpean, Timothy Verstraeten, Lander Willem, Niel Hens, Ann Nowé, Pieter Libin:
Evaluating COVID-19 vaccine allocation policies using Bayesian m-top exploration. CoRR abs/2301.12822 (2023) - [i41]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 abs/2303.03284 (2023) - [i40]Florent Delgrange, Ann Nowé, Guillermo A. Pérez:
Wasserstein Auto-encoded MDPs: Formal Verification of Efficiently Distilled RL Policies with Many-sided Guarantees. CoRR abs/2303.12558 (2023) - [i39]Glenn Ceusters, Muhammad Andy Putratama, Rüdiger Franke, Ann Nowé, Maarten Messagie:
Safe reinforcement learning with self-improving hard constraints for multi-energy management systems. CoRR abs/2304.08897 (2023) - [i38]Axel Abels, Tom Lenaerts, Vito Trianni, Ann Nowé:
Expertise Trees Resolve Knowledge Limitations in Collective Decision-Making. CoRR abs/2305.01063 (2023) - [i37]Willem Röpke, Conor F. Hayes, Patrick Mannion, Enda Howley, Ann Nowé, Diederik M. Roijers:
Distributional Multi-Objective Decision Making. CoRR abs/2305.05560 (2023) - [i36]Qingshuang Sun, Denis Steckelmacher, Yuan Yao, Ann Nowé, Raphaël Avalos:
Dynamic Size Message Scheduling for Multi-Agent Communication under Limited Bandwidth. CoRR abs/2306.10134 (2023) - 2022
- [i35]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 abs/2204.05027 (2022) - [i34]Mathieu Reymond, Eugenio Bargiacchi, Ann Nowé:
Pareto Conditioned Networks. CoRR abs/2204.05036 (2022) - [i33]Glenn Ceusters, Luis Ramirez Camargo, Rüdiger Franke, Ann Nowé, Maarten Messagie:
Safe reinforcement learning for multi-energy management systems with known constraint functions. CoRR abs/2207.03830 (2022) - 2021
- [i32]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 abs/2103.09568 (2021) - [i31]Glenn Ceusters, Román Cantú Rodríguez, Alberte Bouso García, Rüdiger Franke, Geert Deconinck, Lieve Helsen, Ann Nowé, Maarten Messagie, Luis Ramirez Camargo:
Model-predictive control and reinforcement learning in multi-energy system case studies. CoRR abs/2104.09785 (2021) - [i30]Youri Coppens, Denis Steckelmacher, Catholijn M. Jonker, Ann Nowé:
Synthesising Reinforcement Learning Policies through Set-Valued Inductive Rule Learning. CoRR abs/2106.06009 (2021) - [i29]Axel Abels, Tom Lenaerts, Vito Trianni, Ann Nowé:
Dealing with Expert Bias in Collective Decision-Making. CoRR abs/2106.13539 (2021) - [i28]Willem Röpke, Diederik M. Roijers, Ann Nowé, Roxana Radulescu:
Preference Communication in Multi-Objective Normal-Form Games. CoRR abs/2111.09191 (2021) - [i27]Willem Röpke, Diederik M. Roijers, Ann Nowé, Roxana Radulescu:
On Nash Equilibria in Normal-Form Games With Vectorial Payoffs. CoRR abs/2112.06500 (2021) - [i26]Florent Delgrange, Ann Nowé, Guillermo A. Pérez:
Distillation of RL Policies with Formal Guarantees via Variational Abstraction of Markov Decision Processes (Technical Report). CoRR abs/2112.09655 (2021) - [i25]Raphaël Avalos, Mathieu Reymond, Ann Nowé, Diederik M. Roijers:
Local Advantage Networks for Cooperative Multi-Agent Reinforcement Learning. CoRR abs/2112.12458 (2021) - 2020
- [i24]Eugenio Bargiacchi, Timothy Verstraeten, Diederik M. Roijers, Ann Nowé:
Model-based Multi-Agent Reinforcement Learning with Cooperative Prioritized Sweeping. CoRR abs/2001.07527 (2020) - [i23]Roxana Radulescu, Patrick Mannion, Yijie Zhang, Diederik M. Roijers, Ann Nowé:
A utility-based analysis of equilibria in multi-objective normal form games. CoRR abs/2001.08177 (2020) - [i22]Isel Grau, Dipankar Sengupta, María Matilde García Lorenzo, Ann Nowé:
An interpretable semi-supervised classifier using two different strategies for amended self-labeling. CoRR abs/2001.09502 (2020) - [i21]Pieter Libin, Arno Moonens, Timothy Verstraeten, Fabian Perez-Sanjines, Niel Hens, Philippe Lemey, Ann Nowé:
Deep reinforcement learning for large-scale epidemic control. CoRR abs/2003.13676 (2020) - [i20]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 abs/2011.07290 (2020) - 2019
- [i19]Hélène Plisnier, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé:
The Actor-Advisor: Policy Gradient With Off-Policy Advice. CoRR abs/1902.02556 (2019) - [i18]Denis Steckelmacher, Hélène Plisnier, Diederik M. Roijers, Ann Nowé:
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics. CoRR abs/1903.04193 (2019) - [i17]Timothy Verstraeten, Ann Nowé, Jonathan Keller, Yi Guo, Shuangwen Sheng, Jan Helsen:
Fleetwide data-enabled reliability improvement of wind turbines. CoRR abs/1903.11518 (2019) - [i16]Hélène Plisnier, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé:
Transfer Learning Across Simulated Robots With Different Sensors. CoRR abs/1907.07958 (2019) - [i15]Roxana Radulescu, Patrick Mannion, Diederik M. Roijers, Ann Nowé:
Multi-Objective Multi-Agent Decision Making: A Utility-based Analysis and Survey. CoRR abs/1909.02964 (2019) - [i14]Felipe Gomez Marulanda, Pieter Libin, Timothy Verstraeten, Ann Nowé:
IPC-Net: 3D point-cloud segmentation using deep inter-point convolutional layers. CoRR abs/1909.13726 (2019) - [i13]Timothy Verstraeten, Eugenio Bargiacchi, Pieter J. K. Libin, Diederik M. Roijers, Ann Nowé:
Thompson Sampling for Factored Multi-Agent Bandits. CoRR abs/1911.10120 (2019) - [i12]Timothy Verstraeten, Pieter J. K. Libin, Ann Nowé:
Fleet Control using Coregionalized Gaussian Process Policy Iteration. CoRR abs/1911.10121 (2019) - 2018
- [i11]Luisa M. Zintgraf, Diederik M. Roijers, Sjoerd Linders, Catholijn M. Jonker, Ann Nowé:
Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making. CoRR abs/1802.07606 (2018) - [i10]Hélène Plisnier, Denis Steckelmacher, Tim Brys, Diederik M. Roijers, Ann Nowé:
Directed Policy Gradient for Safe Reinforcement Learning with Human Advice. CoRR abs/1808.04096 (2018) - [i9]Axel Abels, Diederik M. Roijers, Tom Lenaerts, Ann Nowé, Denis Steckelmacher:
Dynamic Weights in Multi-Objective Deep Reinforcement Learning. CoRR abs/1809.07803 (2018) - 2017
- [i8]Roxana Radulescu, Peter Vrancx, Ann Nowé:
Analysing Congestion Problems in Multi-agent Reinforcement Learning. CoRR abs/1702.08736 (2017) - [i7]Denis Steckelmacher, Diederik M. Roijers, Anna Harutyunyan, Peter Vrancx, Ann Nowé:
Reinforcement Learning in POMDPs with Memoryless Options and Option-Observation Initiation Sets. CoRR abs/1708.06551 (2017) - [i6]Anna Harutyunyan, Peter Vrancx, Pierre-Luc Bacon, Doina Precup, Ann Nowé:
Learning with Options that Terminate Off-Policy. CoRR abs/1711.03817 (2017) - [i5]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 abs/1711.06299 (2017) - 2015
- [i4]Anna Harutyunyan, Tim Brys, Peter Vrancx, Ann Nowé:
Off-Policy Reward Shaping with Ensembles. CoRR abs/1502.03248 (2015) - [i3]Sofie De Clercq, Steven Schockaert, Martine De Cock, Ann Nowé:
Solving stable matching problems using answer set programming. CoRR abs/1512.05247 (2015) - 2014
- [i2]Anna Harutyunyan, Tim Brys, Peter Vrancx, Ann Nowé:
Off-Policy Shaping Ensembles in Reinforcement Learning. CoRR abs/1405.5358 (2014) - 2013
- [i1]Sofie De Clercq, Steven Schockaert, Martine De Cock, Ann Nowé:
Modeling Stable Matching Problems with Answer Set Programming. CoRR abs/1302.7251 (2013)
Coauthor Index
Rafael Bello 0001
aka: Rafael Bello Pérez
aka: Rafael Bello Pérez
Pieter Libin
aka: Pieter J. K. Libin
aka: Pieter J. K. Libin
María Matilde García Lorenzo
aka: María M. García
aka: María M. García
[j76] [j72] [j67] [j66] [j65] [j63] [j58] [j57] [j56] [c202] [c200] [c199] [c198] [c197] [c196] [c193] [c188] [c183] [c182] [c181] [c174] [c168] [c165] [c160] [c156] [c154] [c152] [c149] [c146] [c145] [c144] [c141] [c138] [c137] [i51] [i47] [i46] [i45] [i44] [i41] [i37] [i35] [i32] [i28] [i27] [i25] [i24] [i23] [i20] [i19] [i18] [i16] [i15] [i13] [i11] [i10] [i9] [i7] [i5]
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