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 | 22 | 2017 |
Deep ordinal reinforcement learning A Zap, T Joppen, J Fürnkranz Machine Learning and Knowledge Discovery in Databases: European Conference …, 2020 | 9 | 2020 |
Preference-based Monte Carlo tree search T Joppen, C Wirth, J Fürnkranz KI 2018: Advances in Artificial Intelligence: 41st German Conference on AI …, 2018 | 9 | 2018 |
Ordinal Monte Carlo Tree Search T Joppen, J Fürnkranz Monte Carlo Search International Workshop, 39-55, 2020 | 3 | 2020 |
Ordinal bucketing for game trees using dynamic quantile approximation T Joppen, T Strübig, J Fürnkranz 2019 IEEE Conference on Games (CoG), 1-8, 2019 | 3 | 2019 |
Informed Hybrid Game Tree Search T Joppen, M Moneke, N Schröder, C Wirth, J Fümkranz Knowledge Engineering Group, Technische Universität Darmstadt, Tech. Rep., 2016 | 1 | 2016 |
An Ordinal Agent Framework T Joppen Technische Universität, 2022 | | 2022 |
Personalized Transaction Kernels for Recommendation Using MCTS M Tavakol, T Joppen, U Brefeld, J Fürnkranz KI 2019: Advances in Artificial Intelligence: 42nd German Conference on AI …, 2019 | | 2019 |
Monte Carlo Tree Search without Numerical Rewards T Joppen | | |