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Tianye Shu
Tianye Shu
Southern University of Science and Technology
Bestätigte E-Mail-Adresse bei mail.sustech.edu.cn
Titel
Zitiert von
Zitiert von
Jahr
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
432021
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
122023
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
102020
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
52022
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
42022
State Space Closure: Revisiting Endless Online Level Generation via Reinforcement Learning
Z Wang, T Shu, J Liu
IEEE Transactions on Games, 2023
22023
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
22022
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
12023
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
12023
Learning to approximate: Auto direction vector set generation for hypervolume contribution approximation
K Shang, T Shu, H Ishibuchi
IEEE Transactions on Evolutionary Computation, 2022
12022
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
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