Quark Mass Models and Reinforcement Learning
Abstract In this paper, we apply reinforcement learning to the problem of constructing models in particle physics. As an example environment, we use the space of Froggatt-Nielsen type models for quark masses. Using a basic policy-based algorithm we show that neural networks can be successfully train...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
SpringerOpen
2021-08-01
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Series: | Journal of High Energy Physics |
Subjects: | |
Online Access: | https://doi.org/10.1007/JHEP08(2021)161 |