首页|期刊导航|Journal of Automation and Intelligence|From black box to physically interpretable:Trustworthy computing for AI-driven decision-making and control
Journal of Automation and Intelligence2026，Vol.5Issue(2)：P.91-111,F0002,22.DOI:10.1016/j.jai.2025.09.003
From black box to physically interpretable:Trustworthy computing for AI-driven decision-making and control
摘要
关键词
Physics-Informed Neural Networks/Physics-Informed Reinforcement Learning/Trustworthy AI/Safety-critical systems分类
信息技术与安全科学引用本文复制引用
Yongduan Song,Anguo Zhang..From black box to physically interpretable:Trustworthy computing for AI-driven decision-making and control[J].Journal of Automation and Intelligence,2026,5(2):P.91-111,F0002,22.基金项目
supported in part by the National Key Research and Development Program of China under Grant 2022YFB4701400/4701401 （）
in part by the Fundamental Research Funds for the Central Universities,China under Project 2024CDJYXTD007 （）
in part by the Graduate Research and Innovation Foundation of Chongqing China under Grant CYS20069 （）
in part by the National Natural Science Foundation of China under Grant 62306001,62403082,and 62250710167 （）
in part by Natural Science Foundation of Fujian Province,China under grant 2025J01290 （）
in part by Chongqing Top-Notch Young Talents Project under Grant cstc2024ycjhbgzxm0085 （）
in part by the Natural Science Foundation of Chongqing,China under Grant CSTB2023NSCQ-LZX0026. （）
