This bears some relationship to looking directly at business process and attempting to control it directly. A kind of context simulation with rewards. Thus similar to game play and process control. I will follow in a post with a real world example.
Reinforcement Learning and AI Good piece with many related examples.
Posted by William Vorhies
Summary: At the core of modern AI, particularly robotics, and sequential tasks is Reinforcement Learning. Although RL has been around for many years it has become the third leg of the Machine Learning stool and increasingly important for Data Scientist to know when and how to implement. ... "
" ... The key to understanding when to use Reinforcement Learning is this:
Data for learning currently does not exist
Or you don’t want to wait to accumulate it (because delay might be costly)
Or the data may change rapidly causing the outcome to change more rapidly than a typical model refresh cycle can accommodate.
What problems fit this description? Well robotic control for one and game play for another, both a central focus of AI over the last few years. ... "
(Read the full article) See also in the WP, which does a good broad overview.