受控系统，提出对提示词、工具或策略的更改，并仅在经过独立评估和批准后才予以保留
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模式： 能够随时间自动分析、修改并改进自身能力与性能的系统
原因： 支持持续优化，减少人工维护，并自动适应需求变化
关键洞察： 结合监控、分析与安全部署机制，实现自主的能力增强
通过这些精选资源加深理解
Self-Instruct: Aligning Language Model with Self Generated Instructions (Wang et al., 2022)
Constitutional AI: Harmlessness from AI Feedback (Bai et al., 2022)
Self-Taught Optimizer (STO): Recursively Self-Improving Code Generation (Zelikman et al., 2023)
Large Language Models Can Self-Improve (Huang et al., 2022)
AI Alignment: A Comprehensive Survey (Ji et al., 2023)
Measuring Progress on Scalable Oversight for Large Language Models (Bowman et al., 2022)
Red Teaming Language Models to Reduce Harms (Ganguli et al., 2022)
Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback (Bai et al., 2022)
Genetic Programming: On the Programming of Computers by Means of Natural Selection (Koza, 1992)
NEAT: Evolving Neural Networks through Augmenting Topologies (Stanley & Miikkulainen, 2002)
Age-Fitness Pareto Optimization (Schmidt & Lipson, 2010)
Automated Algorithm Design via Evolutionary Computation (Pappa et al., 2014)