A reinforcement learning policy agent designs executable agentic workflows by issuing atomic edits to a feedback-providing Workflow Canvas environment.
We need to count such N in the range [1, 1000]
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
FlowSteer: Towards Agents Designing Agentic Workflows via Reinforced Progressive Canvas Editing
A reinforcement learning policy agent designs executable agentic workflows by issuing atomic edits to a feedback-providing Workflow Canvas environment.