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QDEvo integrates Quality-Diversity optimization with LLM-driven heuristic search to overcome mode collapse in automated heuristic design, outperforming state-of-the-art methods on benchmarks and real-world applications.
This paper introduces Minimalist Genetic Programming (MGP), a novel algorithm that replaces evolution with a syntactic derivation process inspired by the Minimalist Program from linguistics, using a MERGE operator to construct symbolic expressions. MGP consistently finds exact ground truth models on symbolic regression tasks where standard GP struggles due to bloat.
The article discusses new research from Sakana AI and Meta on self-improving AI agents, specifically the Darwin-Gödel Machine and Hyperagents, which autonomously rewrite their own code and infrastructure to enhance performance without human intervention.
This paper proposes Dual-Scale Evolutionary Policy Training (DEPT) to address the evolution impasse in social language agents, using asymmetric advantage reshaping to restore gradient signals during self-play.