Assigning credit for delayed payoffs in AI research agents

The author asks how autoresearch agents running hundreds of experiments can credit decisions that pay off much later. Their approach separates what to investigate from how to execute, then learns a transferable value prior to train decisions with reinforcement learning, not just predict progress.