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A more elaborate implementation of this was published years ago, and it wasn't the very first one https://www.science.org/doi/10.1126/science.1165893 https://ww

• thesz 2y ago
  https://arxiv.org/abs/1210.7273 https://arxiv.org/abs/1210.7273 In the article "Distilling free-form natural laws from experimental data", Schmidt and Lipson introduced the idea that free-form natural laws can be learned from experimental measurements in a physical system using symbolic (genetic) regression algorithms. An important claim in this work is that the algorithm finds laws in data without having incorporated any prior knowledge of physics. Upon close inspection, however, we show that their method implicitly incorporates Hamilton's equations of motions and Newton's second law, demystifying how they are able to find Hamiltonians and special classes of Lagrangians from data. I think this is hilarious. I cannot get a PDF of your article and instead I will read a commentary on it which appears to be very interesting.