arXiv cs.AIPaper
AlgoEvo: Self-Evolving Agentic Search for Automated Algorithm Discovery
This is agent architecture for algorithm discovery that learns to reuse patterns across tasks. It outperforms existing frameworks on six benchmarks and handles single and multi-objective problems in one workflow. If you're building agents that need to synthesize or refine code iteratively, the hierarchical experience mechanism is worth studying. The skill decoupling also signals how you should think about agent modularity.