Interactive symbolic regression with co-design mechanism through offline reinforcement learning

Symbolic Regression holds great potential for uncovering underlying mathematical and physical relationships from observed data. However, the vast combinatorial space of possible expressions poses significant challenges for previous online search methods and pre-trained transformer models, which most...

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Vydané v:	Nature communications Ročník 16; číslo 1; s. 3930 - 12
Hlavní autori:	Tian, Yuan, Zhou, Wenqi, Viscione, Michele, Dong, Hao, Kammer, David S., Fink, Olga
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Nature Publishing Group UK 26.04.2025 Nature Publishing Group Nature Portfolio
Predmet:	639/705/1042 639/705/117 Autoregressive models Benchmarks Co-design Combinatorial analysis Humanities and Social Sciences Learning Mathematical models multidisciplinary Regression Regression analysis Reinforcement Science Science (multidisciplinary) Subject specialists
ISSN:	2041-1723, 2041-1723
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