Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/175775
Title: Teachable agent for improving Ikigai
Authors: Chen, Ping
Keywords: Computer and Information Science
Issue Date: 2024
Publisher: Nanyang Technological University
Source: Chen, P. (2024). Teachable agent for improving Ikigai. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175775
Abstract: The global elderly population is projected to more than double by 2050, emphasizing the need for meaningful elderly care. We delved into “Ikigai”, a concept that originated in Japan, signifying an individual’s purpose and satisfaction in life. In this research, we aim to assess and enhance an individual’s Ikigai level. We introduce a knowledge graph-based survey system for dynamic Ikigai assessments, improving response reliability and reflecting Ikigai’s evolving essence. Additionally, we propose a supervised learning model that predicts Ikigai levels from user profiles to help continuous evaluation. For Ikigai enhancement, we propose a teachable agent for the elderly, aiming to stimulate cognitive abilities and heighten self-esteem. Additionally, a reinforcement learning-driven hobby recommender recommends potential Ikigai-boosting activities based on personal attributes. Through a phenomenographic analysis, we explore individual perceptions of these methods, revealing how technology can bolster life’s purpose and meaning. Our pioneering research uniquely fuses advanced techniques with Ikigai exploration.
URI: https://hdl.handle.net/10356/175775
DOI: 10.32657/10356/175775
Schools: School of Computer Science and Engineering 
Rights: This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Theses

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