Iteration Scheduler
A research loop without a scheduler is a queue with delusions. The scheduler is where the loop decides what to stop exploring, and that decision is the whole game. Model a research workflow as a hypothesis queue feeding parallel experiment slots whose results fan back in. Run multiple experiments concurrently with asyncio so the scheduler can keep all slots busy. Score each hypothesis branch with UCB so the scheduler can prune low-yield branches without abandoning exploration. Fan out finished results to a paper-write stage and a re-queue stage so a high-yield branch spawns follow-up hypotheses. Surface a per-iteration trace with branch scores, slot occupancy, and pruning decisions. A flat worklist runs jobs in submission order. That is fine when each job is independent. Research is not independent: a finding from experiment three changes the priority of experiments four and five. A scheduler that reads the result fan-in and reorders the queue gets more useful work done per unit of compute. The interesting design choice is the scoring rule. A greedy scorer always picks the current leader and never explores. A uniform scorer never exploits. UCB (upper confidence bound) is the middle path: exploit the leader while reserving capacity for branches that have been tried less. The queue holds hypotheses. The scheduler picks the highest-UCB hypothesis when a slot frees. Each…
Iteration Scheduler: A research loop without a scheduler is a queue with delusions. The scheduler is where the loop decides what to stop exploring, and that…
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