A reinforcement learning brain storm optimization algorithm (BSO) with learning mechanism
作者：
Highlights：
• A reinforcement learning brain storm optimization algorithm (RLBSO) is proposed.
• Four mutation strategies are introduced to increase the ability of global search.
• Q-learning is utilized to guide the algorithm to the appropriate evolution strategy.
• A self-learning strategy is utilized to determine the update method of the individual.
• The RLBSO algorithm is tested on the CEC 2017 benchmark test suite.
摘要
•A reinforcement learning brain storm optimization algorithm (RLBSO) is proposed.•Four mutation strategies are introduced to increase the ability of global search.•Q-learning is utilized to guide the algorithm to the appropriate evolution strategy.•A self-learning strategy is utilized to determine the update method of the individual.•The RLBSO algorithm is tested on the CEC 2017 benchmark test suite.
论文关键词：Brain storm optimization,Q-learning,Mutation strategies,Self-learning mechanism
论文评审过程：Received 9 February 2021, Revised 1 July 2021, Accepted 30 September 2021, Available online 3 November 2021, Version of Record 18 November 2021.
论文官网地址：https://doi.org/10.1016/j.knosys.2021.107645
