Schmidhuber's Group Releases In-Depth Survey on Agentic Self-Improvement
RobertTLange · x · 2026-08-04
AI researcher Robert T. Lange highly recommends a new in-depth survey on agentic self-improvement from Jürgen Schmidhuber's group.
The survey provides a comprehensive historical overview covering optimization theory, symbolic heuristic self-modification, connectionist meta-learning, and formal frameworks like Schmidhuber's self-referential learning and the Gödel Machine. It transitions into the modern era of LLM and tool-calling agents, exploring language-native self-modification and categorizing contemporary approaches into model improvement and scaffolding improvement. The project also features a living online curated paper library.
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