no code implementations • 15 Jan 2024 • Fei Ming, Wenyin Gong, Ling Wang, Yaochu Jin
By using a Q-Network to learn a policy to estimate the Q-values of all actions, the proposed approach can adaptively select an operator that maximizes the improvement of the population according to the current state and thereby improve the algorithmic performance.
1 code implementation • 13 Dec 2023 • Yanchi Li, Wenyin Gong, Fei Ming, Tingyu Zhang, Shuijia Li, Qiong Gu
Despite the abundance of multitask evolutionary algorithms (MTEAs) proposed for multitask optimization (MTO), there remains a comprehensive software platform to help researchers evaluate MTEA performance on benchmark MTO problems as well as explore real-world applications.