At inference time, the fact extraction agent dynamically augments the graph with only the most informative edges, and thus enables the reasoning agent to identify positive paths effectively and efficiently.
during policy learning, the reasoning agent will be rewarded when reaching the targets, while this positive feedback will also be transferred back to the fact extracting agent if its edge suggestions are adopted by the reasoning agent, i.e.