Agentic data science with the Data Agent Kit
cloud.google.com·7h ago
AI Research
arXiv CS.AI·Jul 29·5 min read
OrchBench: Evaluating Multi-Agent Orchestration Plans in Isolation via Deterministic Simulation
TL;DR
OrchBench is a simulation-based benchmark designed to evaluate multi-agent orchestration plans in isolation, significantly reducing evaluation costs. It demonstrates strong correlation with real-world execution scores while emphasizing the importance of preserving task-critical information over merely increasing agent numbers.
✦ Why It Matters
Use OrchBench to efficiently evaluate and improve your multi-agent orchestration plans today.
Key Takeaways
- Implement OrchBench to benchmark orchestration plans without real execution costs.
- Focus on preserving task-critical information in orchestration strategies.
- Evaluate the diminishing returns of adding more agents in workflows.
- Utilize the strong correlation of simulated scores to refine planning approaches.
How It Works
OrchBench constructs directed acyclic graphs (DAGs) from real-world tasks, encoding dependencies and allowing planners to assign subtasks to agents. The deterministic simulator evaluates these plans without invoking actual agents, providing interpretable metrics on quality and efficiency.