标题
Adaptive operator selection with reinforcement learning
作者
关键词
Artificial bee colony, Adaptive operator selection, Reinforcement learning, Q-learning, Clustering-based Q-learning
出版物
INFORMATION SCIENCES
Volume 581, Issue -, Pages 773-790
出版商
Elsevier BV
发表日期
2021-10-09
DOI
10.1016/j.ins.2021.10.025
参考文献
相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。- Adaptive Memetic Differential Evolution with Niching Competition and Supporting Archive Strategies for Multimodal Optimization
- (2021) Weiguo Sheng et al. INFORMATION SCIENCES
- Machine Learning into Metaheuristics
- (2021) El-Ghazali Talbi ACM COMPUTING SURVEYS
- Hybrid many-objective particle swarm optimization algorithm for green coal production problem
- (2020) Zhihua Cui et al. INFORMATION SCIENCES
- Application of adaptive reliability importance sampling-based extended domain PSO on single mode failure in reliability engineering
- (2020) Bin Bai et al. INFORMATION SCIENCES
- Enhancing MOEA/D with information feedback models for large-scale many-objective optimization
- (2020) Yin Zhang et al. INFORMATION SCIENCES
- An improved MOEA/D algorithm with an adaptive evolutionary strategy
- (2020) Wen-xiang Wang et al. INFORMATION SCIENCES
- Adaptive binary artificial bee colony algorithm
- (2020) Rafet Durgut et al. APPLIED SOFT COMPUTING
- Solving the set-union knapsack problem by a novel hybrid Jaya algorithm
- (2019) Congcong Wu et al. SOFT COMPUTING
- Multifactorial optimization via explicit multipopulation evolutionary framework
- (2019) Genghui Li et al. INFORMATION SCIENCES
- A novel binary artificial bee colony algorithm for the set-union knapsack problem
- (2018) Yichao He et al. Future Generation Computer Systems-The International Journal of eScience
- A Hard C-Means Clustering Algorithm Incorporating Membership KL Divergence and Local Data Information for Noisy Image Segmentation
- (2018) R. R. Gharieb et al. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
- A swarm intelligence-based algorithm for the set-union knapsack problem
- (2018) Fehmi B. Ozsoydan et al. Future Generation Computer Systems-The International Journal of eScience
- Ensemble strategies for population-based optimization algorithms – A survey
- (2018) Guohua Wu et al. Swarm and Evolutionary Computation
- Towards 5G: A Reinforcement Learning-based Scheduling Solution for Data Traffic Management
- (2018) IEEE Transactions on Network and Service Management
- Deep Reinforcement Learning: A Brief Survey
- (2017) Kai Arulkumaran et al. IEEE SIGNAL PROCESSING MAGAZINE
- Landscape-based adaptive operator selection mechanism for differential evolution
- (2017) Karam M. Sallam et al. INFORMATION SCIENCES
- Adaptive composite operator selection and parameter control for multiobjective evolutionary algorithm
- (2016) Qiuzhen Lin et al. INFORMATION SCIENCES
- Dynamic selection of evolutionary operators based on online learning and fitness landscape analysis
- (2016) Pietro A. Consoli et al. SOFT COMPUTING
- The continuous artificial bee colony algorithm for binary optimization
- (2015) Mustafa Servet Kiran APPLIED SOFT COMPUTING
- A novel binary artificial bee colony algorithm based on genetic operators
- (2015) Celal Ozturk et al. INFORMATION SCIENCES
- Adaptive Operator Selection With Bandits for a Multiobjective Evolutionary Algorithm Based on Decomposition
- (2013) Ke Li et al. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
- XOR-based artificial bee colony algorithm for binary optimization
- (2013) Mustafa Servet KIRAN et al. Turkish Journal of Electrical Engineering and Computer Sciences
- DisABC: A new artificial bee colony algorithm for binary optimization
- (2011) Mina Husseinzadeh Kashan et al. APPLIED SOFT COMPUTING
- Analyzing bandit-based adaptive operator selection mechanisms
- (2010) Álvaro Fialho et al. ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE
- Autonomous operator management for evolutionary algorithms
- (2010) Jorge Maturana et al. JOURNAL OF HEURISTICS
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now