arXiv paper "Self-Evolving Agent Harness" formalizes harness self-evolution with admission rules
rohanpaul_ai · x · 2026-10-16
The new arXiv paper "Self-Evolving Agent Harness" (2610.18813, submitted Oct 13) formalizes harness self-evolution: revising an agent's prompts, memory, workflows, and executable components while keeping model weights fixed, with accepted revisions persisting across runs. The framework separates update targets from proposal and admission mechanisms, characterizes search via evolutionary optimization, and examines reliability through continual PAC-learning — yielding, under explicit assumptions, an expected generalization bound, a retention bound conditional on regression budgets, and a high-probability admission rule using fresh independent validation data. It also covers implications for knowledge sharing, scientific reliability, physical safety, and institutional accountability, with a 66-page related-work discussion and continuously updated code.
Related event: New paper formalizes rules for self-evolving agent harnesses(2 posts)→
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