Tim Brys
Tim Brys
Vrije Universiteit Brussel; Action Research Associates
Verified email at - Homepage
Cited by
Cited by
Reinforcement learning from demonstration through shaping
T Brys, A Harutyunyan, HB Suay, S Chernova, ME Taylor, A Now
Twenty-fourth international joint conference on artificial intelligence, 2015
Policy Transfer using Reward Shaping.
T Brys, A Harutyunyan, ME Taylor, A Now
AAMAS, 181-188, 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
Multi-Objectivization of Reinforcement Learning Problems by Reward Shaping
T Brys, A Harutyunyan, P Vrancx, ME Taylor, D Kudenko, A Now
International Joint Conference on Neural Networks, 2014
Distributed learning and multi-objectivity in traffic light control
T Brys, TT Pham, ME Taylor
Connection Science 26 (1), 65-83, 2014
Multi-objectivization and ensembles of shapings in reinforcement learning
T Brys, A Harutyunyan, P Vrancx, A Now, ME Taylor
Neurocomputing 263, 48-59, 2017
Combining multiple correlated reward and shaping signals by measuring confidence
T Brys, A Now, D Kudenko, M Taylor
Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014
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 Now
Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018
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 Now
2014 International joint conference on neural networks (IJCNN), 2306-2314, 2014
Learning Coordinated Traffic Light Control
TT Pham, T Brys, ME Taylor
Adaptive Learning Agents Workshop at AAMAS 2013, 2013
A gentle introduction to reinforcement learning
A Now, T Brys
Scalable Uncertainty Management: 10th International Conference, SUM 2016…, 2016
Fair-Share ILS: A Simple State-of-the-art Iterated Local Search Hyperheuristic.
S Adriaensen, T Brys, A Now
Genetic and Evolutionary Computation Conference (GECCO-14), 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
Dimensionality reduced reinforcement learning for assistive robots
W Curran, T Brys, D Aha, M Taylor, WD Smart
2016 AAAI fall symposium series, 2016
Shaping Mario with Human Advice.
A Harutyunyan, T Brys, P Vrancx, A Now
AAMAS, 1913-1914, 2015
Using PCA to efficiently represent state spaces
W Curran, T Brys, M Taylor, W Smart
arXiv preprint arXiv:1505.00322, 2015
Designing reusable metaheuristic methods: A semi-automated approach
S Adriaensen, T Brys, A Now
2014 IEEE Congress on Evolutionary Computation (CEC), 2969-2976, 2014
On the behaviour of scalarization methods for the engagement of a wet clutch
T Brys, K Van Moffaert, K Van Vaerenbergh, A Now
2013 12th international conference on machine learning and applications 1…, 2013
Off-policy shaping ensembles in reinforcement learning
A Harutyunyan, T Brys, P Vrancx, A Now
ECAI 2014, 1021-1022, 2014
Reinforcement Learning with Heuristic Information
T Brys
Vrije Universiteit Brussel, 2016
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