Towards a framework for computational persuasion with applications in behaviour change

被引:30
|
作者
Hunter, Anthony [1 ]
机构
[1] UCL, Dept Comp Sci, Gower St, London WC1E 6BT, England
基金
英国工程与自然科学研究理事会;
关键词
Computational persuasion; persuasion dialogues; persuasive arguments; dialogical argumentation; computational models of argument; probabilistic argumentation; argumentation strategies;
D O I
10.3233/AAC-170032
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Persuasion is an activity that involves one party trying to induce another party to believe something or to do something. It is an important and multifaceted human facility. Obviously, sales and marketing is heavily dependent on persuasion. But many other activities involve persuasion such as a doctor persuading a patient to drink less alcohol, a road safety expert persuading drivers to not text while driving, or an online safety expert persuading users of social media sites to not reveal too much personal information online. As computing becomes involved in every sphere of life, so too is persuasion a target for applying computer-based solutions. An automated persuasion system (APS) is a system that can engage in a dialogue with a user (the persuadee) in order to persuade the persuadee to do (or not do) some action or to believe (or not believe) something. To do this, an APS aims to use convincing arguments in order to persuade the persuadee. Computational persuasion is the study of formal models of dialogues involving arguments and counterarguments, of user models, and strategies, for APSs. A promising application area for computational persuasion is in behaviour change. Within healthcare organizations, government agencies, and non-governmental agencies, there is much interest in changing behaviour of particular groups of people away from actions that are harmful to themselves and/or to others around them.
引用
收藏
页码:15 / 40
页数:26
相关论文
共 50 条
  • [1] Computational Persuasion with Applications in Behaviour Change
    Hunter, Anthony
    COMPUTATIONAL MODELS OF ARGUMENT, 2016, 287 : 5 - 18
  • [2] Invited Talk: Computational Persuasion with Applications in Behaviour Change
    Hunter, Anthony
    NEW FRONTIERS IN ARTIFICIAL INTELLIGENCE (JSAI-ISAI 2017), 2018, 10838 : 336 - 336
  • [3] Towards a Generic Framework for a Health Behaviour Change Support Agent
    Taj, Fawad
    Klein, Michel C. A.
    Van Halteren, Aart
    ICAART: PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE, VOL 1, 2020, : 311 - 318
  • [4] Challenges to attitude and behaviour change through persuasion
    Hassan, Louise M.
    Michaelidou, Nina
    JOURNAL OF CONSUMER BEHAVIOUR, 2013, 12 (02) : 91 - 92
  • [5] An N-of-1 Evaluation Framework for Behaviour Change Applications
    McCallum, Claire
    Rooksby, John
    Asadzadeh, Parvin
    Gray, Cindy M.
    Chalmers, Matthew
    CHI EA '19 EXTENDED ABSTRACTS: EXTENDED ABSTRACTS OF THE 2019 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, 2019,
  • [6] Opportunities for Argument-Centric Persuasion in Behaviour Change
    Hunter, Anthony
    LOGICS IN ARTIFICIAL INTELLIGENCE, JELIA 2014, 2014, 8761 : 48 - 61
  • [7] Investigating Persuasion in Sustainable Design to Change Behaviour and Attitude
    Wu, Chia-Hsin
    You, Hsiao-Chen
    Deng, Yi-Shin
    NEW WORLD SITUATION: NEW DIRECTIONS IN CONCURRENT ENGINEERING, 2010, : 151 - 159
  • [8] Opportunities for argument-centric persuasion in behaviour change
    Hunter, Anthony
    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, 8761 : 48 - 61
  • [9] Towards Computational Persuasion via Natural Language Argumentation Dialogues
    Hunter, Anthony
    Chalaguine, Lisa
    Czernuszenko, Tomasz
    Hadoux, Emmanuel
    Polberg, Sylwia
    ADVANCES IN ARTIFICIAL INTELLIGENCE, KI 2019, 2019, 11793 : 18 - 33
  • [10] Towards a MOLGENIS based computational framework
    Byelas, Heorhiy
    Kanterakis, Alexandros
    Swertz, Morris
    PROCEEDINGS OF THE 19TH INTERNATIONAL EUROMICRO CONFERENCE ON PARALLEL, DISTRIBUTED, AND NETWORK-BASED PROCESSING, 2011, : 331 - 338