通过终身学习促进自主:对自主智能系统的调查
Dekang Zhu1, Qianyi Bu2, Zhongpan Zhu1,3
1College of Electronic and Information Engineering, Tongji University, Shanghai, China.
Frontiers in neurorobotics
|April 22, 2024
概括
终身学习算法可以在各种应用中提高自主智能系统 (AIS) 的性能. 本综述系统地分析了目前的研究,挑战和整合终身学习与AIS的进展,以期未来的发展.
科学领域:
- 人工智能的人工智能
- 机器学习 机器学习
- 机器人技术 机器人技术 机器人技术
背景情况:
- 终身学习算法越来越多地与自主智能系统 (AIS) 集成.
- 现有的研究摘要对于这个快速发展的领域是不够的.
- 需要进行系统分析,以了解当前的进展和挑战.
研究的目的:
- 对整合终身学习算法和AIS的研究进行彻底的审查和分析.
- 调查各种应用,并评估对AIS性能和可靠性的影响.
- 识别和总结挑战,并讨论创新发展.
主要方法:
- 在AIS中对终身学习算法的综合文献综述.
- 在自动驾驶,异常检测,机器人技术和应急管理方面的应用分析.
- 评估对系统性能和可靠性的影响.
主要成果:
- 在AIS领域确定了终身学习的多种应用.
- 评估了AIS性能和可靠性的提升.
- 总结了AIS在终身学习中遇到的关键挑战.
结论:
- 终身学习显著提高了AIS的能力.
- 进一步的研究和开发以已识别的挑战和创新为指导.
- 本综述为快速发展的领域的研究人员提供了洞察力.
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