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RobustSGPO: Search-Space Control for Agent Harness Evolution

arxiv.org/abs/2609.09646

quality89

Updated 1 h ago · first seen 11 Sept 2026

paper_01M294GK6D9V14YPBQ2JXJM06B

Published
11 Sept 2026
T1 · 1 h ago
arXiv
2609.09646
T1 · 1 h ago
Category
cs.AI
T1 · 1 h ago

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Abstractabstract1

Claim history for Abstract
ValueValid from → toStatusSourceConfidenceExtractor
Semantic-gradient-based prompt optimization (SGPO) improves agent harnesses using execution feedback, but its local update rule leaves the choice of edit scope and operation unresolved. We introduce RobustSGPO, which specifies the requested edit, constructs and checks the patch, and continues search from either the incumbent or retained snapshots. We evaluate permission scheduling, cumulative controls, and task-family transfer in the AgentX brainstorming workflow using 120 tasks, 95 runs, and 7,350 candidate attempts. Periodic $1\to2\to3$ scheduling exceeds fixed maximum permission by 0.28 test-score points. RobustSGPO increases completion on 30 held-out tasks from 60.0% to 80.0% and improves test quality from 3.77 to 4.14 under a 20-million-token budget. Category retention reduces source-task degradation after a shift, whereas random retention reaches a higher destination endpoint. Search-space control benefits quality through executable edits and alternative starting points, with measurable retention overhead.currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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