Cargando…
Branes with Brains: Exploring String Vacua with Deep Reinforcement Learning
We propose deep reinforcement learning as a model-free method for exploring the landscape of string vacua. As a concrete application, we utilize an artificial intelligence agent known as an asynchronous advantage actor-critic to explore type IIA compactifications with intersecting D6-branes. As diff...
| Autores principales: | , , |
|---|---|
| Lenguaje: | eng |
| Publicado: |
2019
|
| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1007/JHEP06(2019)003 http://cds.cern.ch/record/2671898 |