SwarmRSI: Recursive Self-Improvement through Evolving Scientific Agent Swarm
Recursive self-improvement (RSI) in scientific research aims to improve agents' research capabilities through their own experimental experience. Scientific agent swarms can combine evidence and implementations from different research directions to guide their agents' subsequent experiments. However, poor experimental results can leave unclear whether to revise a hypothesis or its implementation, while overall program scores can hide components useful to other agents. To address these challenges, we introduce SwarmRSI, a framework that evolves scientific agent swarms for recursive self-improvement. We devise Feedback-Guided Swarm Mutation to refine hypotheses and their implementations usin...
| Authors | Qianru Meng, Xi Zhang, Konstantinos Papakostas et al. |
|---|---|
| Primary category | cs.AI |
| Published | 14 October 2026 |
| Last updated at source | 14 October 2026 |
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