Speaker
Andre Lukas
(Oxford University)
Description
We present work applying reinforcement learning and genetic algorithms to string model building, specifically to heterotic Calabi-Yau models with monad bundles. Both methods are found to be highly efficient in identifying phenomenologically attractive three-family models, in cases where systematic scans are not feasible. For monads on the bi-cubic Calabi-Yau either method facilitates a complete search of the environment and leads to similar sets of previously unknown three-family models.
Primary author
Andre Lukas
(Oxford University)
