Recursive Environment Scaling for General Long-Horizon Agents
We study environment scaling as a way to increase agent-benchmark difficulty while holding core task objectives fixed.
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Key points
- Our framework, Recursive Environment Scaling (RES), transforms existing benchmark environments while preserving their objectives and completion requirements.
- This produces related environments for paired evaluation and training-trajectory collection.
- Ablations identify recursive inheritance and dependency composition as important contributors to increased difficulty.
- Together, these results support environment scaling for both agent evaluation and training.
Sources (2)
- [1]Recursive Environment Scaling for General Long-Horizon AgentsarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 12, 08:39 AM
We study environment scaling as a way to increase agent-benchmark difficulty while holding core task objectives fixed.
Our framework, Recursive Environment Scaling (RES), transforms existing benchmark environments while preserving their objectives and completion requirements.
- [2]Recursive Environment Scaling for General Long-Horizon AgentsHugging Face Daily Papers · Oct 12, 12:00 AM · same content
Extractive summary: sentences quoted from the sources.
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