Genetic Programming Tree

Genetic programming trees (GPTs) are evolving computational structures used to solve problems by generating and optimizing tree-like programs. Current research focuses on improving GPT efficiency and interpretability, including techniques like sharpness-aware minimization to reduce tree complexity and redundancy, and leveraging large language models to enhance explainability. These advancements are enabling GPTs to tackle increasingly complex tasks, such as predicting material properties and performing high-dimensional symbolic regression, with applications spanning diverse fields from materials science to machine learning. The resulting improvements in both performance and interpretability are driving the adoption of GPTs as a powerful tool for solving real-world problems.