Enhancing Individual Self-Efficacy Through a Self-Growing Memory Artificial Intelligence Agent Integrated with a Diary Application

This paper introduces an artificial intelligence (AI) interactive system featuring a self-growing memory network designed to enhance self-efficacy, reduce loneliness, and maintain social interaction among the elderly. The system dynamically analyzes and processes user-written diaries, generating emp...

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Vydané v:Journal of advanced computational intelligence and intelligent informatics Ročník 29; číslo 1; s. 41 - 52
Hlavní autori: Guo, Yuchen, Siow, Chyan Zheng, Chin, Wei Hong, Hadžić, Bakir, Yorita, Akihiro, Obo, Takenori, Rätsch, Matthias, Kubota, Naoyuki
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Tokyo Fuji Technology Press Co. Ltd 01.01.2025
Predmet:
Artificial intelligence
Diaries
Effectiveness
Feedback loops
Interactive systems
Memory
Mental health
Older people
Psychological factors
Self-efficacy
User experience
ISSN:1343-0130, 1883-8014
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Shrnutí:This paper introduces an artificial intelligence (AI) interactive system featuring a self-growing memory network designed to enhance self-efficacy, reduce loneliness, and maintain social interaction among the elderly. The system dynamically analyzes and processes user-written diaries, generating empathic and personalized responses tailored to each individual. The system architecture includes an experience extraction model, a self-growing memory network that provides a contextual understanding of the user’s daily life, a chat agent, and a feedback loop that adaptively learns the user’s behavioral patterns and emotional states. By drawing on both successful and challenging experiences, the system crafts responses that reinforce the self-efficacy of the user, fostering a sense of accomplishment and engagement. This approach improves the psychological well-being of elderly users and promotes their mental health and overall quality of life through consistent interaction. To validate our proposed method, we developed a diary application to facilitate user interaction and collect diary entries. Over time, the system’s capacity to learn and adapt further refines the user experience, suggesting that AI-driven solutions hold significant potential for mitigating the effects of declining self-efficacy on mental health and social interactions. With the proposed system, we achieve an average system usability scale score of 77.3 (SD = 5.4) and a general self-efficacy scale score of 34.2 (SD = 3.5).
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1343-0130
1883-8014
DOI:10.20965/jaciii.2025.p0041