Evolutionary Multitask Optimization: a Methodological Overview,
Challenges and Future Research Directions

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Evolutionary Multitask Optimization: a Methodological Overview, Challenges and Future Research Directions

4 February 2021

Aritz D. Martinez

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Papers citing "Evolutionary Multitask Optimization: a Methodological Overview, Challenges and Future Research Directions"

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Title
Evolutionary Computation for the Design and Enrichment of General-Purpose Artificial Intelligence Systems: Survey and Prospects Javier Poyatos Javier Del Ser Salvador Garcia H. Ishibuchi Daniel Molina I. Triguero Bing Xue Xin Yao Francisco Herrera 97 1 0 03 Jun 2024
Bayesian Inverse Transfer in Evolutionary Multiobjective Optimization Jiao Liu Abhishek Gupta Yew-Soon Ong 67 0 0 22 Dec 2023
Training Physics-Informed Neural Networks via Multi-Task Optimization for Traffic Density Prediction Bo Wang •. A. K. Qin S. Shafiei Hussein Dia Adriana-Simona Mihaita Hanna Grzybowska PINN AI4CE 63 2 0 08 Jul 2023
Multi-Asset Closed-Loop Reservoir Management Using Deep Reinforcement Learning Y. Nasir L. Durlofsky 59 4 0 21 Jul 2022
A Survey on Learnable Evolutionary Algorithms for Scalable Multiobjective Optimization Songbai Liu Qiuzhen Lin Jianqiang Li Kay Chen Tan 94 56 0 23 Jun 2022
Jack and Masters of all Trades: One-Pass Learning Sets of Model Sets From Large Pre-Trained Models Han Xiang Choong Yew-Soon Ong Abhishek Gupta Caishun Chen Ray Lim 60 5 0 02 May 2022
Evolutionary Multitask Optimization: Fundamental Research Questions, Practices, and Directions for the Future E. Osaba Javier Del Ser Ponnuthurai Nagaratnam Suganthan 79 17 0 29 Nov 2021
Half a Dozen Real-World Applications of Evolutionary Multitasking, and More Abhishek Gupta Lei Zhou Yew-Soon Ong Zefeng Chen Yaqing Hou 70 83 0 27 Sep 2021