4 citations · 6 across the 4 of their papers we have counts for
4 papers
ANCHOR: An External LLM-Driven Supervisory Module Facilitating Healthy Evolution in Self-Evolving Systems
Dianxing Shi, Bowen Wang, Junqi He +2
Self-evolving agents improve through continual self-play and self-generated learning signals, but their internally generated tasks and verifier signals provide limited coverage of…
Estimate Hitting Time by Hitting Probability for Elitist Evolutionary Algorithms
Jun He, Siang Yew Chong, Xin Yao
Drift analysis is a powerful tool for analyzing the time complexity of evolutionary algorithms. However, it requires manual construction of drift functions to bound hitting time fo…
Fast Estimations of Hitting Time of Elitist Evolutionary Algorithms from Fitness Levels
Jun He, Siang Yew Chong, Xin Yao
The fitness level method is a widely used technique for estimating the mean hitting time of elitist evolutionary algorithms on level-based fitness functions. However, this paper id…
Drift Analysis with Fitness Levels for Elitist Evolutionary Algorithms
Jun He, Yuren Zhou
The fitness level method is a popular tool for analyzing the hitting time of elitist evolutionary algorithms. Its idea is to divide the search space into multiple fitness levels an…