| Reinforcement learning from demonstration through shaping T Brys, A Harutyunyan, HB Suay, S Chernova, ME Taylor, A Nowé Twenty-fourth international joint conference on artificial intelligence, 2015 | 296 | 2015 |
| Policy Transfer using Reward Shaping. T Brys, A Harutyunyan, ME Taylor, A Nowé AAMAS, 181-188, 2015 | 110 | 2015 |
| Learning from demonstration for shaping through inverse reinforcement learning HB Suay, T Brys, ME Taylor, S Chernova Proceedings of the 2016 international conference on autonomous agents …, 2016 | 105 | 2016 |
| Multi-Objectivization of Reinforcement Learning Problems by Reward Shaping T Brys, A Harutyunyan, P Vrancx, ME Taylor, D Kudenko, A Nowé International Joint Conference on Neural Networks, 2014 | 98 | 2014 |
| Distributed learning and multi-objectivity in traffic light control T Brys, TT Pham, ME Taylor Connection Science 26 (1), 65-83, 2014 | 74 | 2014 |
| Multi-objectivization and ensembles of shapings in reinforcement learning T Brys, A Harutyunyan, P Vrancx, A Nowé, ME Taylor Neurocomputing 263, 48-59, 2017 | 49 | 2017 |
| Adapting to concept drift in credit card transaction data streams using contextual bandits and decision trees D Soemers, T Brys, K Driessens, M Winands, A Nowé Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 44 | 2018 |
| Combining multiple correlated reward and shaping signals by measuring confidence T Brys, A Nowé, D Kudenko, M Taylor Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014 | 43 | 2014 |
| A novel adaptive weight selection algorithm for multi-objective multi-agent reinforcement learning K Van Moffaert, T Brys, A Chandra, L Esterle, PR Lewis, A Nowé 2014 International joint conference on neural networks (IJCNN), 2306-2314, 2014 | 40 | 2014 |
| A gentle introduction to reinforcement learning A Nowé, T Brys Scalable Uncertainty Management: 10th International Conference, SUM 2016 …, 2016 | 37 | 2016 |
| Learning Coordinated Traffic Light Control TT Pham, T Brys, ME Taylor Adaptive Learning Agents Workshop at AAMAS 2013, 2013 | 36 | 2013 |
| Fair-Share ILS: A Simple State-of-the-art Iterated Local Search Hyperheuristic. S Adriaensen, T Brys, A Nowé Genetic and Evolutionary Computation Conference (GECCO-14), 2014 | 34 | 2014 |
| A conceptual framework for externally-influenced agents: An assisted reinforcement learning review A Bignold, F Cruz, ME Taylor, T Brys, R Dazeley, P Vamplew, C Foale Journal of Ambient Intelligence and Humanized Computing 14 (4), 3621-3644, 2023 | 33 | 2023 |
| Dimensionality reduced reinforcement learning for assistive robots W Curran, T Brys, D Aha, M Taylor, WD Smart 2016 AAAI fall symposium series, 2016 | 26 | 2016 |
| Using PCA to efficiently represent state spaces W Curran, T Brys, M Taylor, W Smart arXiv preprint arXiv:1505.00322, 2015 | 26 | 2015 |
| Shaping Mario with Human Advice. A Harutyunyan, T Brys, P Vrancx, A Nowé AAMAS, 1913-1914, 2015 | 25 | 2015 |
| Designing reusable metaheuristic methods: A semi-automated approach S Adriaensen, T Brys, A Nowé 2014 IEEE Congress on Evolutionary Computation (CEC), 2969-2976, 2014 | 18 | 2014 |
| On the behaviour of scalarization methods for the engagement of a wet clutch T Brys, K Van Moffaert, K Van Vaerenbergh, A Nowé 2013 12th international conference on machine learning and applications 1 …, 2013 | 17 | 2013 |
| Reinforcement Learning with Heuristic Information T Brys Vrije Universiteit Brussel, 2016 | 14 | 2016 |
| Off-policy shaping ensembles in reinforcement learning A Harutyunyan, T Brys, P Vrancx, A Nowé ECAI 2014, 1021-1022, 2014 | 14 | 2014 |
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