Self-Reward Design for SWE Agents

We propose a new approach for software engineering agents to generate and use self-rewards without relying on verifiable rewards. This could promote long-term task achievement and more reliable action selection.

Why it mattersThe appeal lies in reducing reward-design complexity in practical reinforcement learning.