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ORCIDAnn Nowé
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- affiliation: Vrije Universiteit Brussel, Artificial Intelligence Lab, Belgium
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2020 – today
- 2020
[j56]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)- [j55]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) - [j54]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) - [j53]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) - [j52]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) - [c181]Gabriel de Oliveira Ramos, Roxana Radulescu, Ann Nowé, Anderson R. Tavares:
Toll-Based Learning for Minimising Congestion under Heterogeneous Preferences. AAMAS 2020: 1098-1106 - [c180]Timothy Verstraeten, Eugenio Bargiacchi, Pieter J. K. Libin, Diederik M. Roijers, Ann Nowé:
Thompson Sampling for Factored Multi-Agent Bandits. AAMAS 2020: 2029-2031 - [c179]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 - [c178]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 - [c177]Timothy Verstraeten, Pieter J. K. Libin, Ann Nowé:
Fleet Control Using Coregionalized Gaussian Process Policy Iteration. ECAI 2020: 1571-1578 - [c176]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 - [c175]Axel Abels, Tom Lenaerts, Vito Trianni, Ann Nowé:
Collective Decision-Making as a Contextual Multi-armed Bandit Problem. ICCCI 2020: 113-124 - [c174]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 - [c173]Yailen Martínez Jiménez, Jessica Coto Palacio, Ann Nowé:
Multi-Agent Reinforcement Learning Tool for Job Shop Scheduling Problems. OLA 2020: 3-12 - [c172]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 - [c171]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 - [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)
2010 – 2019
- 2019
- [j51]Oliver Roesler, Ann Nowé:
Action learning and grounding in simulated human-robot interactions. Knowl. Eng. Rev. 34: e13 (2019) - [j50]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) - [c170]Youri Coppens, Eugenio Bargiacchi, Ann Nowé:
A Virtual Maze Game to Explain Reinforcement Learning. BNAIC/BENELEARN 2019 - [c169]Jannick Hemelhof, Mihail Mihaylov, Ann Nowé:
Improving Zero-Intelligence Plus for Call Markets. BNAIC/BENELEARN 2019 - [c168]Pieter Libin, Nassim Versbraegen, Ana B. Abecasis, Perpetua Gomes, Tom Lenaerts, Ann Nowé:
Towards a Phylogenetic Measure to Quantify HIV Incidence. BNAIC/BENELEARN 2019 - [c167]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 - [c166]Pieter Libin, Timothy Verstraeten, Diederik M. Roijers, Wenjia Wang, Kristof Theys, Ann Nowé:
Thompson Sampling for m-top Exploration. BNAIC/BENELEARN 2019 - [c165]Regis Loeb, Timothy Verstraeten, Ann Nowé, Ann Dooms:
Privacy Preserving Reinforcement Learning over Distributed Datasets. BNAIC/BENELEARN 2019 - [c164]Jessica Coto Palacio, Yailen Martínez Jiménez, Ann Nowé:
Multi-Agent Reinforcement Learning Tool for Job Shop Scheduling Problems. BNAIC/BENELEARN 2019 - [c163]Hélène Plisnier, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé:
Transfer Reinforcement Learning across Environment Dynamics with Multiple Advisors. BNAIC/BENELEARN 2019 - [c162]Oliver Roesler, Ann Nowé:
Action Learning and Grounding in Simulated Human-Robot Interactions. BNAIC/BENELEARN 2019 - [c161]Willem Röpke, Roxana Radulescu, Kyriakos Efthymiadis, Ann Nowé:
Training a Speech-to-Text Model for Dutch on the Corpus Gesproken Nederlands. BNAIC/BENELEARN 2019 - [c160]Willem Röpke, Roxana Radulescu, Kyriakos Efthymiadis, Ann Nowé:
DuStt - A Speech-to-Text Engine for Dutch. BNAIC/BENELEARN 2019 - [c159]Denis Steckelmacher, Hélène Plisnier, Ann Nowé:
A Motorized Wheelchair that Learns to Make its Way through a Crowd. BNAIC/BENELEARN 2019 - [c158]Denis Steckelmacher, Hélène Plisnier, Diederik M. Roijers, Ann Nowé:
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics. BNAIC/BENELEARN 2019 - [c157]Timothy Verstraeten, Ann Nowé, Jan Helsen:
Failure Avoidance for Wind Turbines through Fleetwide Control. BNAIC/BENELEARN 2019 - [c156]Felipe Gomez Marulanda, Pieter Libin, Timothy Verstraeten, Ann Nowé:
Deep hybrid approach for 3D plane segmentation. ESANN 2019 - [c155]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 - [c154]Axel Abels, Diederik M. Roijers, Tom Lenaerts, Ann Nowé, Denis Steckelmacher:
Dynamic Weights in Multi-Objective Deep Reinforcement Learning. ICML 2019: 11-20 - [c153]Anna Harutyunyan, Peter Vrancx, Philippe Hamel, Ann Nowé, Doina Precup:
Per-Decision Option Discounting. ICML 2019: 2644-2652 - [c152]Pieter Libin, Timothy Verstraeten, Diederik M. Roijers, Wenjia Wang, Kristof Theys, Ann Nowé:
Bayesian Anytime m-top Exploration. ICTAI 2019: 1422-1428 - [c151]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 - [c150]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 - [c149]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 - [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
- [j49]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) - [j48]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) - [j47]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) - [c148]Anna Harutyunyan, Peter Vrancx, Pierre-Luc Bacon, Doina Precup, Ann Nowé:
Learning With Options That Terminate Off-Policy. AAAI 2018: 3173-3182 - [c147]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 - [c146]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 - [c145]Lázaro Lugo, Marilyn Bello, Ann Nowé, Rafael Bello:
A Solution for the Team Selection Problem Using ACO. ANTS Conference 2018: 325-332 - [c144]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 - [c143]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 - [c142]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 - [c141]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 - [c140]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 - [c139]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 - [c138]Christophe Patyn, Thijs Peirelinck, Geert Deconinck, Ann Nowé:
Intelligent Electric Water Heater Control with Varying State Information. SmartGridComm 2018: 1-6 - [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
- [j46]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) - [j45]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) - [j44]Diego S. Comas, Gustavo J. Meschino, Ann Nowé, Virginia L. Ballarin:
Discovering knowledge from data clustering using automatically-defined interval type-2 fuzzy predicates. Expert Syst. Appl. 68: 136-150 (2017) - [j43]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) - [j42]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) - [c137]Elias Fernández Domingos, Juan-Carlos Burguillo, Ann Nowé, Tom Lenaerts:
Coordinating Human and Agent Behavior in Collective-Risk Scenarios. AAAI 2017: 4919-4920 - [c136]Diederik M. Roijers, Luisa M. Zintgraf, Ann Nowé:
Interactive Thompson Sampling for Multi-objective Multi-armed Bandits. ADT 2017: 18-34 - [c135]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 - [c134]Roxana Radulescu, Peter Vrancx, Ann Nowé:
Analysing Congestion Problems in Multi-agent Reinforcement Learning. AAMAS 2017: 1705-1707 - [c133]Leticia Arco, Gladys Casas, Ann Nowé:
Clustering methodology for smart metering data based on local and global features. IML 2017: 65:1-65:13 - [c132]Steven Adriaensen, Filip Moons, Ann Nowé:
An Importance Sampling Approach to the Estimation of Algorithm Performance in Automated Algorithm Design. LION 2017: 3-17 - [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) - 2016
- [j41]Marilyn Bello-García, Rafael Bello, María Matilde García Lorenzo, Ann Nowé:
Personnel Selection in a Competitive Environment. Computación y Sistemas 20(2) (2016) - [j40]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) - [j39]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) - [j38]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) - [j37]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) - [j36]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) - [c131]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 - [c130]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 - [c129]Sofie De Clercq, Steven Schockaert, Ann Nowé, Martine De Cock:
Formalizing Commitment-Based Deals in Boolean Games. ECAI 2016: 329-337 - [c128]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 - [c127]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 - [c126]Steven Adriaensen, Ann Nowé:
Towards a White Box Approach to Automated Algorithm Design. IJCAI 2016: 554-560 - [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
- [j35]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) - [j34]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) - [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 - [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
- [j33]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) - [j32]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) - [j31]Kristof Van Moffaert, Ann Nowé:
Multi-objective reinforcement learning using sets of pareto dominating policies. J. Mach. Learn. Res. 15(1): 3483-3512 (2014) - [c107]