New survey maps how agentic systems are learning to improve themselves
SchmidhuberAI · x · 2026-07-21
What the survey covers
The post introduces a new survey, “Self-Improvements in Modern Agentic Systems,” which reviews how classic ideas like meta-learning and recursive self-improvement are being revived by foundation models.
It links to the paper, project page, and GitHub repo, positioning the work as a broad look at how agentic systems are evolving through:
- Intrinsic generative demonstrations
- Intrinsic evaluative feedback
- Extrinsic exploratory experience
The accompanying figure maps a 2023–2026 landscape of methods across FM improvement and scaffolding improvement, showing a fast-expanding research area around memory, tools, prompting, and agent design.
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