agent/papers/items/2026-2607-11565-heuristic-learning-for-active-flow-control-using-coding-agents.md

Paper: Heuristic Learning for Active Flow Control Using Coding Agents

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type: paper title: Heuristic Learning for Active Flow Control Using Coding Agents authors: Paul Garnier, Jonathan Viquerat, Elie Hachem year: 2026 venue: arXiv url: https://arxiv.org/abs/2607.11565 code_url: source: arxiv collected_at: 2026-07-27 published_at: 2026-07-13 updated_at: 2026-07-13 status: queued relevance: high topics:

• agent-evaluation
• coding-agent
• tool-use
• world-model methods:

benchmarks:

models:

datasets:

• cs.LG related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 13 collection_queries: coding-agent

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: coding-agent
• inferred topics: agent-evaluation, coding-agent, tool-use, world-model
• arXiv categories: cs.LG
• collection score: 13

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2607.11565