3 papers
cs.NE2025
Learning Where, What and How to Transfer: A Multi-Role Reinforcement Learning Approach for Evolutionary Multitasking
Jiajun Zhan, Zeyuan Ma, Yue-Jiao Gong +1
Evolutionary multitasking (EMT) algorithms typically require tailored designs for knowledge transfer, in order to assure convergence and optimality in multitask optimization. In th…
cs.NE2025
A New Scope and Domain Measure Comparison Method for Global Convergence Analysis in Evolutionary Computation
Liu-Yue Luo, Zhi-Hui Zhan, Kay Chen Tan +1
Convergence analysis is a fundamental research topic in evolutionary computation (EC). The commonly used analysis method models the EC algorithm as a homogeneous Markov chain for a…
cs.NE2025
Toward Automated Algorithm Design: A Survey and Practical Guide to Meta-Black-Box-Optimization
Zeyuan Ma, Hongshu Guo, Yue-Jiao Gong +2
In this survey, we introduce Meta-Black-Box-Optimization~(MetaBBO) as an emerging avenue within the Evolutionary Computation~(EC) community, which incorporates Meta-learning approa…