Adaptive User Interfaces

Abstract

According to various embodiments, user performance and / or motivation for a computing system may be maximized by optimizing one or more target components of a user interface of the computing system. The target components may be aspects of the user interface that is perceived by the user. One or more input features and one or more output features may be identified, and data regarding these input and output features may be gathered. This data may be compared with the results generated by a set of candidate artificial intelligence algorithms to determine which of them provides the best fit with the data collected. Then, the selected artificial intelligence algorithm may be applied to the user interface to iteratively change the target components over time until the optimal settings for each user are discovered.

Description

CROSS-REFERENCE TO RELATED APPLICATION[0001]The present application claims priority as a continuation of U.S. patent application Ser. No. 13 / 916,600 for “Adaptive User Interfaces,” Attorney Docket No. INS002, filed Jun. 13, 2013, the disclosure of which is incorporated by reference herein, in its entirety.[0002]The present application is related to U.S. Utility application Ser. No. 13 / 590,000 for “Hierarchical Based Sequencing Machine Learning Model”, filed Aug. 20, 2012, the disclosure of which is incorporated by reference herein, in its entirety.[0003]The present application is related to U.S. Utility application Ser. No. 13 / 725,653 for “Instance Weighted Learning Machine Learning Model”, filed Dec. 21, 2012, the disclosure of which is incorporated by reference herein, in its entirety.[0004]The present application is related to U.S. Pat. No. 8,352,389 for “Multiple Output Relaxation Machine Learning Model”, filed Aug. 20, 2012 and issued Jan. 8, 2013, the disclosure of which is in...

AI Technical Summary

Benefits of technology

[0011]According to various embodiments of the present invention, systems and methods are provided to actively adapt to the user, so as to customize the user experience in real-time. The user experience can be adapted by changing system behaviors and / or aesthetics in order to maximize the motivation and performance of the user. Motivation may be measured in terms of activity levels (system use), where performance can be measured in terms of activity outcomes (such as sales made, games won, etc.). These adaptive user interfaces can be used to maximize user experience and performance for any application that has at least one of the following characteristics:

Problems solved by technology

Accordingly, a “one size fits all” reward system may leave some users relatively unaffected.

Accordingly, designing an optimal reward system, according to known methods, may take many hours' research with the involvement of diverse experts, focus groups of users, and considerable trial and error.

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