Machine Learning As a Blind Creator of Infinite Algebras in the Context of Strings Theory

Abstract

This paper, presents the scenario that basic algorithms based at the principles of Machine Learning can massively produce a huge amount of algebras. The case of Witt algebra has been focused. Once this algebra is reformulated with the inclusion of real numbers, operations of commutation are derived. Thus, once the modified Witt algebra exhibits the dependence of exponential shapes, some approximations are applied. The projections of this onto an algorithm based on the criteria of Tom Mitchell have produced a huge amount of valid algebras. In this manner is seen that although Machine Learning can be efficient to produce theoretical tools, most of them might be unnecessary to consolidate a theory. Therefore, in scenarios by which Artificial Intelligence is adopted as a tool to study theoretical physics, might be seen as factory of everything but far away of realistic physics models.