Dynamic User Interface Personalization Based on Deep Reinforcement Learning

Personalization is one of the most sought out and popular methods for brand recognition and consumer attraction. The usage of deep reinforcement learning due to its' ability to learn actions the way humans learn from experience, if utilized and evaluated properly it can result in a revolutionary effect on personalization. The methodology proposed in this research utilizes deep reinforcement learning where an artificial agent may be trained by interacting with its environment. Utilizing the experience gathered, the agent is able optimize in the form of rewards. The approach explained, can be utilized across applications which can be personalized. Several scenarios ranging from changing the layout of webpages, to rearranging icons on mobile home screens are discussed. The main objective is to develop an API for the web developers and smartphone manufacturers to utilize so that depending on the application personalization can be achieved by enhancing saliency, minimizing selection time, increasing engagement, or an arrangement of these. The technique can manage a variety of adaptations, such as how graphical elements are shown and how they behave. An experiment was conducted which showcased improved user experience considering the position change of the user interface elements thereby personalizing the layout.

I. Introduction

The escalation of the cyberspace has resulted in numerous changes in our day to day lives. Perhaps the foremost crucial benefaction was the infinite, quick and free availability of information. As time passed, more and more information becomes available for users. As a result, information has grown vastly with the exponential development of the internet and the distinction of rich and useful information out of the worthless information has become a mindless task for the users [2]. A user's ultimate goal is to access the information they need efficiently without any inconvenience.