Please use this identifier to cite or link to this item:
Title: Acceptance of repeated automated advice
Authors: Yeo, Li Ting
Keywords: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Yeo, L. T. (2022). Acceptance of repeated automated advice. Final Year Project (FYP), Nanyang Technological University, Singapore.
Abstract: Modern life is filled with multiple automated advisers, from GPS navigators to trip-booking services to news alerts. Many of them try to adapt to dynamic preferences of their users, some only allow the user to modify their behaviour or advice preferences. Neither is very successful. In this project, we will try to take another look into why that happens. The conjecture is that the acceptance of advice is changing over time. The project will create a controlled advice environment (in a game form) that will allow to test whether and how the acceptance of automated advice changes over time, whether it depends on performance only or the length of interaction itself, which of these parameters is prevalent. The project can concentrate on the creating the environment only (more programming) and expand into a more research oriented variant (studying behaviour models, comparing their performance, etc.)
Schools: School of Computer Science and Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
SCSE FYP Report - Yeo Li Ting.pdf
  Restricted Access
1.88 MBAdobe PDFView/Open

Page view(s)

Updated on Feb 20, 2024

Download(s) 50

Updated on Feb 20, 2024

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.