MAP: A computational model for adaptive persuasion
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 provides a unified framework for different persuasion strategies. Specifically, persuasion is not adaptable to the indivi...
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sg-smu-ink.sis_research-64722020-12-24T03:00:54Z MAP: A computational model for adaptive persuasion KANG, Yilin TAN, Ah-hwee 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 provides 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 user study show that MAP-based agents are able to change others’ attitudes and behaviors intentionally, interpret individual differences between users, and adapt to user’s behavior for effective persuasion. 2015-05-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5469 info:doi/10.5555/2772879.2773479 https://ink.library.smu.edu.sg/context/sis_research/article/6472/viewcontent/finalsubmittion.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Agent Adaptive Persuasion Social behavior Databases and Information Systems Theory and Algorithms |
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Agent Adaptive Persuasion Social behavior Databases and Information Systems Theory and Algorithms KANG, Yilin TAN, Ah-hwee MAP: A computational model for adaptive persuasion |
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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 provides 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 user study show that MAP-based agents are able to change others’ attitudes and behaviors intentionally, interpret individual differences between users, and adapt to user’s behavior for effective persuasion. |
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KANG, Yilin TAN, Ah-hwee |
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KANG, Yilin TAN, Ah-hwee |
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KANG, Yilin |
title |
MAP: A computational model for adaptive persuasion |
title_short |
MAP: A computational model for adaptive persuasion |
title_full |
MAP: A computational model for adaptive persuasion |
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MAP: A computational model for adaptive persuasion |
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MAP: A computational model for adaptive persuasion |
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map: a computational model for adaptive persuasion |
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Institutional Knowledge at Singapore Management University |
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2015 |
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https://ink.library.smu.edu.sg/sis_research/5469 https://ink.library.smu.edu.sg/context/sis_research/article/6472/viewcontent/finalsubmittion.pdf |
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