mlsanityData to 7 Oct 2026

RobustSGPO: Search-Space Control for Agent Harness Evolution

arXiv 2609.09646 ↗First posted 9 Sep 2026cs.AIcited by 1

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Abstract (arXiv)

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→2→3 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.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 7 of its 14 references that are in the map. First posted on arXiv 9 Sep 2026.

Builds on

7 of 14 references.

References · 7

  1. 2023Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolutioncited by 521
  2. 2015Illuminating search spaces by mapping elitescited by 406
  3. 2026Self-Harness: Harnesses That Improve Themselvescited by 79
  4. 2026Adaptive Auto-Harness: Sustained Self-Improvement for Agentic System Deployment on Open-Ended Task Streamscited by 20
  5. 2026Harness-Aware Self-Evolving: Co-Evolving Model Weights, Harness, and Task Solutionscited by 10
  6. 2026AgentX: Towards Agent-Driven Self-Iteration of Industrial Recommender Systemscited by 8
  7. 2026HELIX: Model-Harness Co-evolution for Recursive Self-Improvementcited by 6

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