Artificial Intelligence

Toward Training Superintelligent Software Agents through Self-Play SWE-RL

Current LLM-based software engineering agents rely heavily on human-curated data (e.g., GitHub issues, pull requests) and environments (e.g., test suites), which limits their path to superintelligence. The paper introduces Self-play SWE-RL (SSR), a reinforcement learning framework that trains a single …