From Simulation to Strategy: Automating Personalized Interaction Planning for Conversational Agents

Fuente: arXiv

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Detalles Bibliográficos
Autores principales:	Chang, Wen-Yu, Huang, Tzu-Hung, Chen, Chih-Ho, Chen, Yun-Nung
Formato:	Preprint
Publicado:	2025
Materias:	Computation and Language
Acceso en línea:	Acceder al recurso
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_version_	1866914181366677504
author	Chang, Wen-Yu Huang, Tzu-Hung Chen, Chih-Ho Chen, Yun-Nung
author_facet	Chang, Wen-Yu Huang, Tzu-Hung Chen, Chih-Ho Chen, Yun-Nung
contents	Amid the rapid rise of agentic dialogue models, realistic user-simulator studies are essential for tuning effective conversation strategies. This work investigates a sales-oriented agent that adapts its dialogue based on user profiles spanning age, gender, and occupation. While age and gender influence overall performance, occupation produces the most pronounced differences in conversational intent. Leveraging this insight, we introduce a lightweight, occupation-conditioned strategy that guides the agent to prioritize intents aligned with user preferences, resulting in shorter and more successful dialogues. Our findings highlight the importance of rich simulator profiles and demonstrate how simple persona-informed strategies can enhance the effectiveness of sales-oriented dialogue systems.
format	Preprint
id	arxiv_https___arxiv_org_abs_2510_08621
institution	arXiv
publishDate	2025
record_format	arxiv
spellingShingle	From Simulation to Strategy: Automating Personalized Interaction Planning for Conversational Agents Chang, Wen-Yu Huang, Tzu-Hung Chen, Chih-Ho Chen, Yun-Nung Computation and Language Amid the rapid rise of agentic dialogue models, realistic user-simulator studies are essential for tuning effective conversation strategies. This work investigates a sales-oriented agent that adapts its dialogue based on user profiles spanning age, gender, and occupation. While age and gender influence overall performance, occupation produces the most pronounced differences in conversational intent. Leveraging this insight, we introduce a lightweight, occupation-conditioned strategy that guides the agent to prioritize intents aligned with user preferences, resulting in shorter and more successful dialogues. Our findings highlight the importance of rich simulator profiles and demonstrate how simple persona-informed strategies can enhance the effectiveness of sales-oriented dialogue systems.
title	From Simulation to Strategy: Automating Personalized Interaction Planning for Conversational Agents
topic	Computation and Language
url	https://arxiv.org/abs/2510.08621

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