91 citations · 92 across the 5 of their papers we have counts for
5 papers
SDDMO-Bench: A Benchmark Suite for Streaming Data-Driven Dynamic Multi-Objective Optimization
Wenjie Xiao, Hui Bai, Junhao Chen
Streaming data-driven dynamic multi-objective optimization requires algorithms to track time-varying Pareto fronts using only sequential observations under concept drift. However,…
Decision Variable Analysis-Guided Differentiated Fuzzy Search for Large-Scale Multi-Objective Optimization
Boxi Xiao, Hui Bai, Jinhua Zheng +2
Large-scale multi-objective optimization problems (LSMOPs) are challenging due to their high-dimensional decision spaces. Fuzzy search is an effective technique for improving searc…
Generalized Population-Based Training for Hyperparameter Optimization in Reinforcement Learning
Hui Bai, Ran Cheng
Hyperparameter optimization plays a key role in the machine learning domain. Its significance is especially pronounced in reinforcement learning (RL), where agents continuously int…
Evolutionary Reinforcement Learning: A Survey
Hui Bai, Ran Cheng, Yaochu Jin
Reinforcement learning (RL) is a machine learning approach that trains agents to maximize cumulative rewards through interactions with environments. The integration of RL with deep…
Lamarckian Platform: Pushing the Boundaries of Evolutionary Reinforcement Learning towards Asynchronous Commercial Games
Hui Bai, Ruimin Shen, Yue Lin +2
Despite the emerging progress of integrating evolutionary computation into reinforcement learning, the absence of a high-performance platform endowing composability and massive par…