5 things about self-evolution in DR agents

Self-evolution improves individual agents to provide high-quality contextual information.

Self-evolution encourages the exploration of diverse knowledge.

The self-evolutionary algorithm is applied to each component of the workflow.

Self-evolution mitigates information loss for each unit agent throughout long trajectories.

The component-wise optimization enhances the quality of each step in the research workflow.