What-if scenario based and generative adversarial network generated design adaptation

Patent metadata

Field	Value
Publication number	US-12548205-B2
Application number	US-202217659024-A
Country	US
Kind code	B2
Filing date	Apr 13, 2022
Priority date	Apr 13, 2022
Publication date	Feb 10, 2026
Grant date	Feb 10, 2026

Abstract

A computer-implemented method, a computer program product, and a computer system for design adaptation. One or more computing devices receive images provided by a user, receive form a designer one or more designer provided what-if scenarios of a design related to the images, receive form the user one or more user selected what-if scenarios from the one or more designer provided what-if scenarios, and retrieve information about influencing factors form an artificial intelligence (AI) knowledge corpus, where the influencing factors affect qualities of the images. One or more computing devices input the retrieved information into a generative adversarial network (GAN) module. One or more computing devices change the images by the GAN module to generate adapted images for the one or more user selected what-if scenarios, based on the retrieved information.

First claim

What is claimed is:

1 . A computer-implemented method for what-if scenario based and generative adversarial network (GAN) generated design adaptation, the method comprising:
receiving images provided by a user; receiving, from a designer, one or more designer provided what-if scenarios for a user interface design that includes the images; receiving, from the user, one or more user selected what-if scenarios from the one or more designer provided what-if scenarios; retrieving, from an artificial intelligence (AI) knowledge corpus, influencing factors corresponding to the one or more user selected what-if scenarios, wherein the influencing factors are related to image qualities; retrieving, from the AI knowledge corpus, user preferences corresponding to the one or more user selected what-if scenarios; inputting the user preferences, the images, and the influencing factors into a GAN module; changing the images, by the GAN module and based on the input, to generate adapted images for the one or more user selected what-if scenarios; and providing adapted user interface designs comprising the one or more user selected what-if scenarios with the adapted images.

2 . The computer-implemented method of claim 1 , further comprising:
receiving, from the user, feedback on the adapted user interface designs.

3 . The computer-implemented method of claim 2 , further comprising:
in response to determining, based on the feedback, that the user is satisfied with an adapted user interface design from the adapted user interface designs, updating the knowledge corpus with user positive feedback.

4 . The computer-implemented method of claim 2 , further comprising:
in response to determining, based on the feedback, that the user is not satisfied with the adapted user interface designs, updating the knowledge corpus with user negative feedback.

5 . The computer-implemented method of claim 2 , further comprising:
in response to determining, based on the feedback, that the user is not satisfied with the adapted user interface designs, requesting, from the designer, one or more new what-if scenarios for the user interface design; receive, from the designer and in response to the request, one or more designer newly provided what-if scenarios for the user interface design; receiving, from the user, one or more user newly selected what-if scenarios from the one or more designer newly provided what-if scenarios; and iterating steps of the what-if scenario based and GAN generated design adaptation to generate at least one additional adapted user interface design.

6 . The computer-implemented method of claim 2 , further comprising:
in response to determining, based on the feedback, that the user is not satisfied with the adapted user interface designs, receiving, from the user, one or more new user selected what-if scenarios from the one or more designer provided what-if scenarios; and iterating steps of the what-if scenario based and GAN generated design adaptation to generate at least one additional adapted user interface design.

7 . A computer program product for what-if scenario based and generative adversarial network (GAN) generated design adaptation, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by one or more processors, the program instructions executable to:
receive images provided by a user; receive, from a designer, one or more designer provided what-if scenarios for a user interface design that includes the images; receive, from the user, one or more user selected what-if scenarios from the one or more designer provided what-if scenarios; retrieve, from an artificial intelligence (AI) knowledge corpus, influencing factors corresponding to the one or more user selected what-if scenarios, wherein the influencing factors are related to image qualities; retrieve, from the AI knowledge corpus, user preferences corresponding to the one or more user selected what-if scenarios; input the user preferences, the one or more user selected what-if scenarios, the images, and the influencing factors into a GAN module; change the images, by the GAN module and based on the input, to generate adapted images for the one or more user selected what-if scenarios; and provide adapted user interface designs comprising the one or more user selected what-if scenarios with the adapted images.

8 . The computer program product of claim 7 , wherein the program instructions are further executable to:
receive, from the user, feedback on the adapted user interface designs.

9 . The computer program product of claim 8 , wherein he program instructions are further executable to:
in response to determining, based on the feedback, that the user is satisfied with an adapted user interface design from the adapted user interface designs, update the knowledge corpus with user positive feedback.

10 . The computer program product of claim 8 , wherein the program instructions are further executable to:
in response to determining, based on the feedback, that the user is not satisfied with the adapted user interface designs, update the knowledge corpus with user negative feedback.

11 . The computer program product of claim 8 , wherein the program instructions are further executable to:
in response to determining, based on the feedback, that the user is not satisfied with the adapted user interface designs, request, from the designer, one or more new what-if scenarios for the user interface design; receive, from the designer and in response to the request, one or more designer newly provided what-if scenarios for the user interface design; receive, from the user, one or more user newly selected what-if scenarios from the one or more designer newly provided what-if scenarios; and iterate steps of the what-if scenario based and GAN generated design adaptation to generate additional adapted user interface designs until the user is satisfied with one or more of the additional adapted user interface designs.

12 . The computer program product of claim 8 , wherein the program instructions are further executable to:
in response to determining, based on the feedback, that the user is not satisfied with the adapted user interface designs, obtain, from the user, one or more new user selected what-if scenarios from the one or more designer provided what-if scenarios; and iterate steps of the what-if scenario based and GAN generated design adaptation to generate additional adapted user interface designs until the user is satisfied with one or more of the additional adapted user interface designs.

13 . A computer system for what-if scenario based and generative adversarial network (GAN) generated design adaptation, the computer system comprising one or more processors, one or more computer readable tangible storage devices, and program instructions stored on at least one of the one or more computer readable tangible storage devices for execution by at least one of the one or more processors, the program instructions executable to:
receive images provided by a user; receive, from a designer, one or more designer provided what-if scenarios for a user interface design that includes the images; receive, from the user, one or more user selected what-if scenarios from the one or more designer provided what-if scenarios; retrieve, from an artificial intelligence (AI) knowledge corpus, influencing factors corresponding to the one or more user selected what-if scenarios, wherein the influencing factors are related to image qualities; retrieve, from the AI

Assignees

• IBM

Inventors

• Mene Atul
• Fox Jeremy R
• Agrawal Tushar
• Rakshit Sarbajit K

Classifications

• G06N3/045

  Combinations of networks · CPC title

• G06N3/042

  Knowledge-based neural networks; Logical representations of neural networks · CPC title

• G06T2200/24

  involving graphical user interfaces [GUIs] · CPC title

• G06N3/0475

  Generative networks · CPC title

• G06N3/088

  Non-supervised learning, e.g. competitive learning · CPC title