| Experience-driven PCG via reinforcement learning: A Super Mario Bros study T Shu, J Liu, GN Yannakakis 2021 IEEE Conference on Games (CoG), 1-9, 2021 | 39 | 2021 |
| Benchmarking large-scale subset selection in evolutionary multi-objective optimization K Shang, T Shu, H Ishibuchi, Y Nan, LM Pang Information Sciences 622, 755-770, 2023 | 11 | 2023 |
| A novel cnet-assisted evolutionary level repairer and its applications to Super Mario Bros T Shu, Z Wang, J Liu, X Yao 2020 IEEE Congress on Evolutionary Computation (CEC), 1-10, 2020 | 10 | 2020 |
| Effects of archive size on computation time and solution quality for multi-objective optimization T Shu, K Shang, H Ishibuchi, Y Nan IEEE Transactions on Evolutionary Computation, 2022 | 4 | 2022 |
| Reinforcement learning with dual-observation for general video game playing C Hu, Z Wang, T Shu, H Tong, J Togelius, X Yao, J Liu IEEE Transactions on Games, 2022 | 4 | 2022 |
| Two-Phase Procedure for Efficiently Removing Dominated Solutions From Large Solution Sets T Shu, Y Nan, K Shang, H Ishibuchi Proceedings of the Genetic and Evolutionary Computation Conference, 740-748, 2023 | 1 | 2023 |
| State Space Closure: Revisiting Endless Online Level Generation via Reinforcement Learning Z Wang, T Shu, J Liu IEEE Transactions on Games, 2023 | 1 | 2023 |
| Two-stage greedy approximated hypervolume subset selection for large-scale problems Y Nan, H Ishibuchi, T Shu, K Shang International Conference on Evolutionary Multi-Criterion Optimization, 391-404, 2023 | 1 | 2023 |
| Learning to approximate: Auto direction vector set generation for hypervolume contribution approximation K Shang, T Shu, H Ishibuchi IEEE Transactions on Evolutionary Computation, 2022 | 1 | 2022 |
| Direction Vector Selection for R2-Based Hypervolume Contribution Approximation T Shu, K Shang, Y Nan, H Ishibuchi International Conference on Parallel Problem Solving from Nature, 110-123, 2022 | 1 | 2022 |
| Analysis of Partition Methods for Dominated Solution Removal from Large Solution Sets T Shu, Y Nan, K Shang, H Ishibuchi 2023 IEEE Symposium Series on Computational Intelligence (SSCI), 441-448, 2023 | | 2023 |
| Ensemble R2-based Hypervolume Contribution Approximation G Wu, T Shu, Y Nan, K Shang, H Ishibuchi 2023 IEEE Symposium Series on Computational Intelligence (SSCI), 1503-1510, 2023 | | 2023 |
| Empirical Hypervolume Optimal µ-Distributions on Complex Pareto Fronts K Shang, T Shu, G Wu, Y Nan, LM Pang, H Ishibuchi 2023 IEEE Symposium Series on Computational Intelligence (SSCI), 433-440, 2023 | | 2023 |
| Normalization in R2-Based Hypervolume and Hypervolume Contribution Approximation G Wu, T Shu, K Shang, H Ishibuchi 2023 IEEE Symposium Series on Computational Intelligence (SSCI), 449-456, 2023 | | 2023 |
| Two-Stage Lazy Greedy Inclusion Hypervolume Subset Selection for Large-Scale Problem Y Nan, T Shu, H Ishibuchi 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2023 | | 2023 |
| Effects of External Archives on the Performance of Multi-Objective Evolutionary Algorithms on Real-World Problems Y Nan, T Shu, H Ishibuchi 2023 IEEE Congress on Evolutionary Computation (CEC), 1-8, 2023 | | 2023 |
| Benchmarking subset selection from large candidate solution sets in evolutionary multi-objective optimization K Shang, T Shu, H Ishibuchi, Y Nan, LM Pang arXiv preprint arXiv:2201.06700, 2022 | | 2022 |
| Robust Reinforcement Learning for General Video Game Playing. C Hu, Z Wang, T Shu, Y Tao, H Tong, J Togelius, X Yao, J Liu CoRR, 2020 | | 2020 |
