Digital Information Recommendation System Activated by Reinforcement Learning in Society

Abstract

The Internet, multimedia applications and digital devices have been ubiquitous in our society. Most people have their own PCs and can easily access to the World Wide Web site or on-line news. A system that can learn what information or programs a viewer wants or enjoys and that can then recommend them to the viewer would be a solution to the situations. In this paper, problems with conventional approaches are made clear by analyzing conventional methods of recommendation. Introducing reinforcement learning in society enables the system to recommend two kinds of serious programs. An evaluation of the new method is presented.