基础模型和智能决策:进展,挑战和前景
Jincai Huang1,2, Yongjun Xu3,4,5, Qi Wang3,4,5
1College of Systems Engineering, National University of Defense Technology, Changsha 410073, China.
Innovation (Cambridge (Mass.))
|June 18, 2025
概括
智能决策 (IDM) 利用人工智能 (AI) 和基础模型 (FMs) 进行适应性选择. 这项调查探讨了AI.
科学领域:
- 人工智能的人工智能
- 决策科学 决策科学 决策科学
背景情况:
- 智能决策 (IDM) 对于自动化和增强复杂流程至关重要.
- 现代IDM利用先进的框架,如AI代理和强化学习来进行适应性选择.
- 基础模型 (FMs) 越来越多地集成,统一各种数据模式,以加强决策.
研究的目的:
- 调查智能决策 (IDM) 的发展情况.
- 检查结合基础模型 (FMs) 的高级IDM范式.
- 突出FM对科学和工业领域决策的变革性影响.
主要方法:
- 综述了基于多式联运基础的多式联运方法的近期进展.
- 对人工智能代理和高级强化学习框架的分析.
- 检查各种输入方式 (视觉,语言,感官数据) 的整合.
主要成果:
- 基础模型 (FMs) 是关键的,改变了决策和研究能力.
- 大规模的多式联运机数据处理促进了适应性和跨学科的突破.
- 具有FM的IDM在医疗保健,生命科学和教育方面产生了重大影响.
结论:
- 基础模型代表了智能决策的重大进步.
- 集成FM使决策过程更具适应性和有效性.
- 未来的工作重点应该是建立高效,适应性和道德决策系统.
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