AI RESEARCH
SeaEvo: Advancing Algorithm Discovery with Strategy Space Evolution
arXiv CS.AI
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ArXi:2604.24372v1 Announce Type: cross LLM-guided evolutionary search has emerged as a promising paradigm for automated algorithm discovery, yet most systems track search progress primarily through executable programs and scalar fitness. Even when natural-language reflection is used, it is often used locally in mutation prompts or d without an explicit population-level organization of strategic directions.