02860nam 2200505 450 991069865350332120230731000328.03-031-27019-39783031270192(ebook)10.1007/978-3-031-27019-2(CKB)5590000001037559(DE-He213)978-3-031-27019-2(MiAaPQ)EBC7236713(Au-PeEL)EBL7236713(PPN)269660666(EXLCZ)99559000000103755920230731d2023 uy 0engurnn#---mamaatxtrdacontentcrdamediacrrdacarrierArtificial Intelligence for Scientific Discoveries Extracting Physical Concepts from Experimental Data Using Deep Learning /Raban ItenFirst edition.Cham, Switzerland :Springer,[2023]©20231 online resource illustrations3-031-27018-5 9783031270185 Includes bibliographical references.Introduction -- Machine Learning Background -- Overview of Using Machine Learning for Physical Discoveries -- Theory: Formalizing the Process of Human Model Building -- Methods: Using Neural Networks to Find Simple Representations -- Applications: Physical Toy Examples -- Open Questions and Future Prospects.Will research soon be done by artificial intelligence, thereby making human researchers superfluous? This book explains modern approaches to discovering physical concepts with machine learning and elucidates their strengths and limitations. The automation of the creation of experimental setups and physical models, as well as model testing are discussed. The focus of the book is the automation of an important step of the model creation, namely finding a minimal number of natural parameters that contain sufficient information to make predictions about the considered system. The basic idea of this approach is to employ a deep learning architecture, SciNet, to model a simplified version of a physicist's reasoning process. SciNet finds the relevant physical parameters, like the mass of a particle, from experimental data and makes predictions based on the parameters found. The author demonstrates how to extract conceptual information from such parameters, e.g., Copernicus' conclusion that the solar system is heliocentric. .Artificial intelligenceDiscoveries in scienceArtificial intelligence.Discoveries in science.006.3Iten Raban1352779MiAaPQMiAaPQMiAaPQBOOK9910698653503321Artificial Intelligence for Scientific Discoveries3200556UNINA