14 citations · 25 across the 6 of their papers we have counts for
6 papers
MetaDE: Evolving Differential Evolution by Differential Evolution
Minyang Chen, Chenchen Feng, and Ran Cheng
As a cornerstone in the Evolutionary Computation (EC) domain, Differential Evolution (DE) is known for its simplicity and effectiveness in handling challenging black-box optimizati…
ParetoTracker: Understanding Population Dynamics in Multi-objective Evolutionary Algorithms through Visual Analytics
Zherui Zhang, Fan Yang, Ran Cheng +1
Multi-objective evolutionary algorithms (MOEAs) have emerged as powerful tools for solving complex optimization problems characterized by multiple, often conflicting, objectives. W…
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…
Mitigating Task Interference in Multi-Task Learning via Explicit Task Routing with Non-Learnable Primitives
Chuntao Ding, Zhichao Lu, Shangguang Wang +2
Multi-task learning (MTL) seeks to learn a single model to accomplish multiple tasks by leveraging shared information among the tasks. Existing MTL models, however, have been known…
Rethinking Population-assisted Off-policy Reinforcement Learning
Bowen Zheng, Ran Cheng
While off-policy reinforcement learning (RL) algorithms are sample efficient due to gradient-based updates and data reuse in the replay buffer, they struggle with convergence to lo…
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…