Explore/benchmark/RestoreBench: Can AI Agents Restore Power Flow Convergence?
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Riccardo Mansutti, Andrea Pomarico, Robert Jakob, Qian Zhang, Alberto Berizzi, Kevin O'Sullivan/RestoreBench: Can AI Agents Restore Power Flow Convergence?Unknown

RestoreBench is a benchmark that evaluates AI agents’ ability to diagnose and fix non‑convergent power flow problems, providing a simulation environment, observation and action spaces, and metrics for multiple LLMs and agent architectures.

benchmark
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Production readinessResearch / EarlyBest for exploration and prototyping.
Risk notesUnknown licenseVerify license before production use.
AgentHub Score
55 / 100
Composite score from 6 signals. How we score →
Active project
55Score
Growth
40C
Activity
30C
Documentation
70C+
Maturity
45C
Community
42C
Production
58C
GitHub stars · 0 days observed0 not enough history
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not enough history
Repository activity · 0 days observednot enough history from pushed_at
inactivepushed
not enough history
not enough history
Practical assessment
Should you use it?

✓ Best for

  • Research and experimentation
  • Prototype development
  • Learning agentic patterns

◎ Strengths

  • Active community
  • Open source
  • Well-documented API

✕ Not ideal for

  • Untested at scale without validation
  • Teams without AI/ML expertise

⚠ Watch-outs

  • Review changelog before updating
  • Verify license for commercial use
Technical details
What's inside
Language
License
Sourcearxiv
Open source✗ No
Commercial use
Docs
Demo

AgentHub Score

55
Score 55/100
Below average

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