| UBY-a large-scale unified lexical-semantic resource based on LMF I Gurevych, J Eckle-Kohler, S Hartmann, M Matuschek, CM Meyer, C Wirth Proceedings of the 13th Conference of the European Chapter of the …, 2012 | 159 | 2012 |
| A survey of preference-based reinforcement learning methods C Wirth, R Akrour, G Neumann, J Fürnkranz The Journal of Machine Learning Research 18 (1), 4945-4990, 2017 | 72 | 2017 |
| Model-free preference-based reinforcement learning C Wirth, J Fürnkranz, G Neumann Thirtieth AAAI Conference on Artificial Intelligence, 2016 | 49 | 2016 |
| EPMC: Every visit preference Monte Carlo for reinforcement learning C Wirth, J Fürnkranz Asian Conference on Machine Learning, 483-497, 2013 | 15 | 2013 |
| Informed hybrid game tree search for general video game playing T Joppen, MU Moneke, N Schröder, C Wirth, J Fürnkranz IEEE Transactions on Games 10 (1), 78-90, 2017 | 14 | 2017 |
| Preference-based reinforcement learning: A preliminary survey C Wirth, J Fürnkranz Proceedings of the ECML/PKDD-13 Workshop on Reinforcement Learning from …, 2013 | 14 | 2013 |
| On learning from game annotations C Wirth, J Fürnkranz IEEE Transactions on Computational Intelligence and AI in Games 7 (3), 304-316, 2014 | 10 | 2014 |
| A policy iteration algorithm for learning from preference-based feedback C Wirth, J Fürnkranz International Symposium on Intelligent Data Analysis, 427-437, 2013 | 6 | 2013 |
| First steps towards learning from game annotations C Wirth, J Fürnkranz | 5 | 2012 |
| Preference-Based Monte Carlo Tree Search T Joppen, C Wirth, J Fürnkranz Joint German/Austrian Conference on Artificial Intelligence (Künstliche …, 2018 | 3 | 2018 |
| Efficient Preference-based Reinforcement Learning C Wirth Technische Universität, 2017 | 2 | 2017 |
| Informed Hybrid Game Tree Search T Joppen, M Moneke, N Schröder, C Wirth, J Fürnkranz Knowledge Engineering Group, Technische Universität Darmstadt, Tech. Rep., 2016 | 1 | 2016 |
| Learning from trajectory-based action preferences C Wirth, J Fürnkranz Proceedings of the ICRA 2013 Workshop on Autonomous Learning (to appear, 2013 | 1 | 2013 |
| Efficient Preference-based Reinforcement Learning: Using Surrogates for Solving Markov Decision Processes with Preferences C Wirth Technische Universität Darmstadt, 2017 | | 2017 |
| Preference Learning from Annotated Game Databases. C Wirth, J Fürnkranz LWA, 57-68, 2014 | | 2014 |
| Stroke-und Trimap-basierte Mattingverfahren A Eigenstetter, C Wirth | | 2008 |
