Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

5-2015

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 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.

Keywords

Agent, Adaptive, Persuasion, Social behavior

Discipline

Databases and Information Systems | Theory and Algorithms

Research Areas

Data Science and Engineering

Publication

Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015, Istanbul Congress Center Istanbul, Turkey, May 4-8

Volume

3

First Page

1871

Last Page

1872

ISBN

9781450337717

Identifier

10.5555/2772879.2773479

Publisher

International Foundation for Autonomous Agents and Multiagent Systems

City or Country

Istanbul, Turkey

Download

Share

COinS