Publications -> Conference Papers

An Adaptive Computational Model for Personalized Persuasion


Authors: Y. Kang, A.-H. Tan, and C. Miao
Title: An Adaptive Computational Model for Personalized Persuasion
Abstract: While a variety of persuasion agents have been created and applied in different domains such as marketing, military training and health industry, there is a lack of a model which can provide a unified framework for different persuasion strategies. Specifically, persuasion is not adaptable to the individuals’ personal states in different situations. Grounded in the Elaboration Likelihood Model (ELM), this paper presents a computational model called Model for Adaptive Persuasion (MAP) for virtual agents. MAP is a semi-connected network model which enables an agent to adapt its persuasion strategies through feedback. We have implemented and evaluated a MAP-based virtual nurse agent who takes care and recommends healthy lifestyle habits to the elderly. Our experimental results show that the MAP-based agent is able to change the others’ attitudes and behaviors intentionally, interpret individual differences between users, and adapt to user’s behavior for effective persuasion.
Keywords: 
Conference Name: 24th International Joint Conference on Artificial Intelligence (IJCAI'15)
Location: Buenos Aires, Argentina
Publisher: AAAI Press
Year: 2015
Accepted PDF File: An_Adaptive_Computational_Model_for_Personalized_Persuasion_accepted.pdf
Permanent Link: http://ijcai.org/papers15/Papers/IJCAI15-016.pdf
Reference: Y. Kang, A.-H. Tan, and C. Miao, “An adaptive computational model for personalized persuasion,” in Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI’15). AAAI Press, July 2015, pp. 61–67.
bibtex: 
@inproceedings{LILY-c44, 
   author	= {Kang, Yilin and Tan, Ah-Hwee and Miao, Chunyan},
   title	= {An Adaptive Computational Model for Personalized Persuasion},  
   booktitle	= {Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI'15)}, 
   year		= {2015}, 
   month	= {July}, 
   pages	= {61-67}, 
   location	= {Buenos Aires, Argentina},
   publisher	= {AAAI Press},
}