A Novel CNet-assisted Evolutionary Level Repairer and Its Applications to Super Mario Bros. - Tianye Shu; Ziqi Wang 005; Jialin Liu 001; Xin Yao 001 (CEC, 2020)

Robust Reinforcement Learning for General Video Game Playing. - Chengpeng Hu; Ziqi Wang 005; Tianye Shu; Yang Tao; Hao Tong; Julian Togelius; Xin Yao 001; Jialin Liu 001 (CoRR, 2020)

Experience-Driven PCG via Reinforcement Learning: A Super Mario Bros Study. - Tianye Shu; Jialin Liu 001; Georgios N. Yannakakis (CoG, 2021)

Direction Vector Selection for R2-Based Hypervolume Contribution Approximation. - Tianye Shu; Ke Shang; Yang Nan 001; Hisao Ishibuchi (PPSN (2), 2022)

Benchmarking Subset Selection from Large Candidate Solution Sets in Evolutionary Multi-objective Optimization. - Ke Shang; Tianye Shu; Hisao Ishibuchi; Yang Nan 001; Lie Meng Pang (CoRR, 2022)

Effects of Archive Size on Computation Time and Solution Quality for Multi-Objective Optimization. - Tianye Shu; Ke Shang; Hisao Ishibuchi; Yang Nan 001 (CoRR, 2022)

Effects of External Archives on the Performance of Multi-Objective Evolutionary Algorithms on Real-World Problems. - Yang Nan 001; Tianye Shu; Hisao Ishibuchi (CEC, 2023)

Two-Stage Greedy Approximated Hypervolume Subset Selection for Large-Scale Problems. - Yang Nan 001; Hisao Ishibuchi; Tianye Shu; Ke Shang (EMO, 2023)

Two-Phase Procedure for Efficiently Removing Dominated Solutions From Large Solution Sets. - Tianye Shu; Yang Nan 001; Ke Shang; Hisao Ishibuchi (GECCO, 2023)

Two-Stage Lazy Greedy Inclusion Hypervolume Subset Selection for Large-Scale Problem. - Yang Nan 001; Tianye Shu; Hisao Ishibuchi (SMC, 2023)

Empirical Hypervolume Optimal µ-Distributions on Complex Pareto Fronts. - Ke Shang; Tianye Shu; Guotong Wu; Yang Nan 001; Lie Meng Pang; Hisao Ishibuchi (SSCI, 2023)

Analysis of Partition Methods for Dominated Solution Removal from Large Solution Sets. - Tianye Shu; Yang Nan 001; Ke Shang; Hisao Ishibuchi (SSCI, 2023)

Ensemble R2-based Hypervolume Contribution Approximation. - Guotong Wu; Tianye Shu; Yang Nan 001; Ke Shang; Hisao Ishibuchi (SSCI, 2023)

Normalization in R2-Based Hypervolume and Hypervolume Contribution Approximation. - Guotong Wu; Tianye Shu; Ke Shang; Hisao Ishibuchi (SSCI, 2023)

Effects of Archive Size on Computation Time and Solution Quality for Multiobjective Optimization. - Tianye Shu; Ke Shang; Hisao Ishibuchi; Yang Nan 001 (IEEE Trans. Evol. Comput., 2023)

Benchmarking large-scale subset selection in evolutionary multi-objective optimization. - Ke Shang; Tianye Shu; Hisao Ishibuchi; Yang Nan 001; Lie Meng Pang (Inf. Sci., 2023)

Reinforcement Learning With Dual-Observation for General Video Game Playing. - Chengpeng Hu; Ziqi Wang 005; Tianye Shu; Hao Tong; Julian Togelius; Xin Yao 001; Jialin Liu 001 (IEEE Trans. Games, 2023)

Performance Evaluation of Evolutionary Multi-Objective Algorithms Using Real-World Problems with an Additional Total Constraint Violation Objective. - Yang Nan 001; Hisao Ishibuchi; Tianye Shu (CEC, 2024)

Interactive Final Solution Selection in Multi-Objective Optimization. - Cheng Gong; Yang Nan 001; Tianye Shu; Lie Meng Pang; Hisao Ishibuchi; Qingfu Zhang 001 (CEC, 2024)

Last-X-Generation Archiving Strategy for Multi-Objective Evolutionary Algorithms. - Tianye Shu; Yang Nan 001; Ke Shang; Hisao Ishibuchi (CEC, 2024)

Analysis of Real-World Constrained Multi-Objective Problems and Performance Comparison of Multi-Objective Algorithms. - Yang Nan 001; Hisao Ishibuchi; Tianye Shu; Ke Shang (GECCO, 2024)

Gradient-Guided Local Search for IGD/IGDPlus Subset Selection. - Yang Nan 001; Hisao Ishibuchi; Tianye Shu; Ke Shang (GECCO, 2024)

Learning Pareto Set for Multi-Objective Continuous Robot Control. - Tianye Shu; Ke Shang; Cheng Gong; Yang Nan 001; Hisao Ishibuchi (IJCAI, 2024)

LTR-HSS: A Learning-to-Rank Based Framework for Hypervolume Subset Selection. - Cheng Gong; Ping Guo 007; Tianye Shu; Qingfu Zhang 001; Hisao Ishibuchi (PPSN (4), 2024)

On the use of the Total Constraint Violation as an Additional Objective in Evolutionary Multi-Objective Optimization. - Yang Nan 001; Hisao Ishibuchi; Tianye Shu; Cheng Gong (SMC, 2024)

Learning to Approximate: Auto Direction Vector Set Generation for Hypervolume Contribution Approximation. - Ke Shang; Tianye Shu; Hisao Ishibuchi (IEEE Trans. Evol. Comput., 2024)

State-Space Closure: Revisiting Endless Online Level Generation via Reinforcement Learning. - Ziqi Wang 005; Tianye Shu; Jialin Liu 001 (IEEE Trans. Games, 2024)

Shape of Feasible Regions of Real-World Multi-Objective Problems. - Yang Nan 001; Hisao Ishibuchi; Tianye Shu (CEC, 2025)

On the Quality of Large Non-dominated Archives. - Ke Shang; Tianye Shu; Yang Nan 001; Lie Meng Pang; Hisao Ishibuchi (CEC, 2025)

Numerical Analysis of Pareto Set Modeling. - Tianye Shu; Hisao Ishibuchi; Yang Nan 001; Lie Meng Pang (EMO (2), 2025)

R2 Indicator Analysis using the Optimal Distributions of Solutions for R2 and Other Indicators. - Yang Nan 001; Hisao Ishibuchi; Tianye Shu; Ke Shang (GECCO, 2025)

Gradient-Guided Local Search for Large-Scale Hypervolume Subset Selection. - Yang Nan 001; Tianye Shu; Hisao Ishibuchi; Ke Shang (IEEE Trans. Evol. Comput., 2025)