R2SAEA fine-tunes an LLM with RL to reason about solution relations for surrogate-assisted evolutionary optimization, reporting improved relation prediction and SOTA performance on single- and multi-objective benchmarks.
Surrogate-assisted evolutionary computation: Recent advances and future challenges
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SEETO achieves 6% better hypervolume in NWP parameter calibration with only 20 evaluations by using meteorological state representations for bi-level knowledge transfer from similar past tasks.
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Relation Reasoning with LLMs in Expensive Optimization
R2SAEA fine-tunes an LLM with RL to reason about solution relations for surrogate-assisted evolutionary optimization, reporting improved relation prediction and SOTA performance on single- and multi-objective benchmarks.