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BiBTeX citation export for TUEC4: Test of Machine Learning at the CERN LINAC4

@inproceedings{kain:hb2021-tuec4,
  author       = {V. Kain and N. Bruchon and S. Hirlaender and N. Madysa and P.K. Skowroński and G. Valentino and I. Vojskovic},
% author       = {V. Kain and N. Bruchon and S. Hirlaender and N. Madysa and P.K. Skowroński and G. Valentino and others},
% author       = {V. Kain and others},
  title        = {{Test of Machine Learning at the CERN LINAC4}},
  booktitle    = {Proc. HB'21},
  pages        = {181--185},
  eid          = {TUEC4},
  language     = {english},
  keywords     = {controls, linac, electron, target, network},
  venue        = {Batavia, IL, USA},
  series       = {ICFA ABDW on High-Intensity and High-Brightness Hadron Beams},
  number       = {64},
  publisher    = {JACoW Publishing, Geneva, Switzerland},
  month        = {04},
  year         = {2022},
  issn         = {2673-5571},
  isbn         = {978-3-95450-225-7},
  doi          = {10.18429/JACoW-HB2021-TUEC4},
  url          = {https://jacow.org/hb2021/papers/tuec4.pdf},
  abstract     = {{The CERN H⁻ linear accelerator, LINAC4, served as a test bed for advanced algorithms during the CERN Long Shutdown 2 in the years 2019/20. One of the main goals was to show that reinforcement learning with all its benefits can be used as a replacement for numerical optimization and as a complement to classical control in the accelerator control context. Many of the algorithms used were prepared beforehand at the electron line of the AWAKE facility to make the best use of the limited time available at LINAC4. An overview of the algorithms and concepts tested at LINAC4 and AWAKE will be given and the results discussed.}},
}