Mathematical intuition, deep learning, and Robbins' problem
F. Thomas Bruss
TL;DR
The present article is an essay about mathematical intuition and Artificial intelligence, followed by a guided excursion to Robbins’ Problem of Optimal Stopping, to guide readers through the probabilistic intuition behind Robbins’ problem and to show why A.I., and in particular Deep Learning, may contribute an essential part in its solution.
Abstract
{\bf Abstract.} The present article is an essay about mathematical intuition and Artificial intelligence (A.I.), followed by a guided excursion to a well-known open problem. It has two objectives. The first is to reconcile the way of thinking of a computer program as a sequence of mathematically defined instructions with what we face nowadays with newer developments. The second and major goal is to guide interested readers through the probabilistic intuition behind Robbins' problem and to show why A.I., and in particular Deep Learning, may contribute an essential part in its solution. This article contains no new mathematical results, and no implementation of deep learning either. Nevertheless, we hope to find through its semi-historic narrative style, with well-known examples and an easily accessible terminology, the interest of mathematicians of different inclinations.