dailyai.report

ReVEL clusters candidate heuristics into behaviorally coherent groups to give compact feedback. It then feeds these summaries to a large language LLM that reasons over multiple turns. The model proposes new heuristic tweaks, which the evolutionary algorithm evaluates and selects. The approach yields heuristics that outperform hand‑crafted baselines on benchmark NP‑hard problems.