Hostname: page-component-8448b6f56d-t5pn6 Total loading time: 0 Render date: 2024-04-19T22:05:38.463Z Has data issue: false hasContentIssue false
  • English
  • Français

Measuring the strength of threats, rewards, and appeals in persuasive negotiation dialogues

Published online by Cambridge University Press:  12 November 2020

Mariela Morveli-Espinoza Open the ORCID record for Mariela Morveli-Espinoza [Opens in a new window] ,
Juan Carlos Nieves Open the ORCID record for Juan Carlos Nieves [Opens in a new window]  and
Cesar Augusto Tacla Open the ORCID record for Cesar Augusto Tacla [Opens in a new window]
Mariela Morveli-Espinoza
Affiliation:
Program in Electrical and Computer Engineering (CPGEI), Federal University of Technology, Paraná (UTFPR), Curitiba, Brazil, e-mails: morveli.espinoza@gmail.com; tacla@utfpr.edu.br
Juan Carlos Nieves
Affiliation:
Department of Computing Science of Umeå University, Umeå, Sweden, e-mail: jcnieves@cs.umu.se
Cesar Augusto Tacla
Affiliation:
Program in Electrical and Computer Engineering (CPGEI), Federal University of Technology, Paraná (UTFPR), Curitiba, Brazil, e-mails: morveli.espinoza@gmail.com; tacla@utfpr.edu.br
Get access Rights & Permissions [Opens in a new window]

Abstract

The aim of this article is to propose a model for the measurement of the strength of rhetorical arguments (i.e., threats, rewards, and appeals), which are used in persuasive negotiation dialogues when a proponent agent tries to convince his opponent to accept a proposal. Related articles propose a calculation based on the components of the rhetorical arguments, that is, the importance of the goal of the opponent and the certainty level of the beliefs that make up the argument. Our proposed model is based on the pre-conditions of credibility and preferability stated by Guerini and Castelfranchi. Thus, we suggest the use of two new criteria for the strength calculation: the credibility of the proponent and the status of the goal of the opponent in the goal processing cycle. We use three scenarios in order to illustrate our proposal. Besides, the model is empirically evaluated and the results demonstrate that the proposed model is more efficient than previous works of the state of the art in terms of numbers of negotiation cycles, number of exchanged arguments, and number of reached agreements.

Type
Research Article
Information
The Knowledge Engineering Review , Volume 35 , 2020 , e36
Copyright
© The Author(s), 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Allen, M., Bruflat, R., Fucilla, R., Kramer, M., McKellips, S., Ryan, D. J. & Spiegelhoff, M. 2000. Testing the persuasiveness of evidence: combining narrative and statistical forms. Communication Research Reports 17(4), 331–336.CrossRefGoogle Scholar
Amgoud, L. 2003. A formal framework for handling conflicting desires. In ECSQARU, 2711, 552–563. Springer.CrossRefGoogle Scholar
Amgoud, L. & Besnard, P. 2013. A formal characterization of the outcomes of rule-based argumentation systems. In International Conference on Scalable Uncertainty Management, 78–91. Springer.CrossRefGoogle Scholar
Amgoud, L., Parsons, S. & Maudet, N. 2000. Arguments, dialogue, and negotiation. In Proceedings of the 14th European Conference on Artificial Intelligence, 338–342.Google Scholar
Amgoud, L. & Prade, H. 2004. Threat, reward and explanatory arguments: generation and evaluation. In Proceedings of the ECAI Workshop on Computational Models of Natural Argument, 73–76.Google Scholar
Amgoud, L. & Prade, H. 2005a. Formal handling of threats and rewards in a negotiation dialogue. In Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, 529–536. ACM.CrossRefGoogle Scholar
Amgoud, L. & Prade, H. 2005b. Handling threats, rewards, and explanatory arguments in a unified setting. International Journal of Intelligent Systems 20(12), 1195–1218.CrossRefGoogle Scholar
Amgoud, L. & Prade, H. 2006. Formal handling of threats and rewards in a negotiation dialogue. In Argumentation in Multi-Agent Systems, 88–103. Springer.CrossRefGoogle Scholar
Baarslag, T., Hendrikx, M. J., Hindriks, K. V. & Jonker, C. M. 2016. Learning about the opponent in automated bilateral negotiation: a comprehensive survey of opponent modeling techniques. Autonomous Agents and Multi-Agent Systems 30(5), 849–898.CrossRefGoogle Scholar
Blusi, M. & Nieves, J. C. 2019. Feasibility and acceptability of smart augmented reality assisting patients with medication pillbox self-management. In Studies in Health Technology and Informatics, 521–525.Google Scholar
Busch, M., Schrammel, J. & Tscheligi, M. 2013. Personalized persuasive technology–development and validation of scales for measuring persuadability. In International Conference on Persuasive Technology, 33–38. Springer.CrossRefGoogle Scholar
Castelfranchi, C. & Guerini, M. 2007. Is it a promise or a threat? Pragmatics & Cognition 15(2), 277–311.CrossRefGoogle Scholar
Castelfranchi, C. & Paglieri, F. 2007. The role of beliefs in goal dynamics: prolegomena to a constructive theory of intentions. Synthese 155(2), 237–263.CrossRefGoogle Scholar
Cialdini, R. 2016. Pre-Suasion: A Revolutionary Way to Influence and Persuade. Simon and Schuster.Google Scholar
Cialdini, R. B. 2007. Influence: The psychology of persuasion, 55. Collins.Google Scholar
Dimopoulos, Y. & Moraitis, P. 2011. Advances in argumentation based negotiation. In Negotiation and Argumentation in Multi-agent Systems: Fundamentals, Theories, Systems and Applications, 82–125.Google Scholar
Falcone, R. & Castelfranchi, C. 2001. Social trust: a cognitive approach. In Trust and Deception in Virtual Societies, 55–90. Springer.CrossRefGoogle Scholar
Falcone, R. & Castelfranchi, C. 2004. Trust dynamics: how trust is influenced by direct experiences and by trust itself. In Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 740–747. IEEE.Google Scholar
Florea, A. M. & Kalisz, E. 2007. Adaptive negotiation based on rewards and regret in a multi-agent environment. In International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, 2007. SYNASC, 254–259. IEEE.CrossRefGoogle Scholar
Guerini, M. & Castelfranchi, C. 2006. Promises and threats in persuasion. In 6th Workshop on Computational Models of Natural Argument, 14–21.Google Scholar
Hadjinikolis, C., Modgil, S. & Black, E. 2015. Building support-based opponent models in persuasion dialogues. In International Workshop on Theories and Applications of Formal Argumentation, 128–145. Springer.CrossRefGoogle Scholar
Hadjinikolis, C., Siantos, Y., Modgil, S., Black, E. & McBurney, P. 2013. Opponent modelling in persuasion dialogues. In IJCAI.Google Scholar
Hunter, A. 2015. Modelling the persuadee in asymmetric argumentation dialogues for persuasion. In Proceedings of the 24th International Joint Conference on Artificial Intelligence, 3055–3061.Google Scholar
Ingeson, M., Blusi, M. & Nieves, J. C. 2018. Microsoft hololens-a mhealth solution for medication adherence. In International Workshop on Artificial Intelligence in Health, 99–115. Springer.CrossRefGoogle Scholar
Kaptein, M., Markopoulos, P., de Ruyter, B. & Aarts, E. 2009. Can you be persuaded? individual differences in susceptibility to persuasion. In IFIP Conference on Human-Computer Interaction, 115–118. Springer.CrossRefGoogle Scholar
Lam, H.-P. & Governatori, G. 2011. What are the necessity rules in defeasible reasoning? In International Conference on Logic Programming and Nonmonotonic Reasoning, 187–192. Springer.CrossRefGoogle Scholar
Morveli-Espinoza, M., Nieves, J. C. & Tacla, C. A. 2020. Measuring the strength of rhetorical arguments. In To be published in the Proceedings of the 17th European Conference on Multi-Agent Systems. International Foundation for Autonomous Agents and Multiagent Systems.Google Scholar
Morveli-Espinoza, M., Possebom, A. T. & Tacla, C. A. 2016. Construction and strength calculation of threats. In Computational Models of Argument - Proceedings of COMMA 2016, Potsdam, Germany, 12–16 September, 2016, 403–410.Google Scholar
Morveli-Espinoza, M., Possebom, A. T. & Tacla, C. A. 2019. On the calculation of the strength of threats. Knowledge and Information Systems 62(4), 1511–1538.CrossRefGoogle Scholar
OKeefe, D. J. 2018. Message pretesting using assessments of expected or perceived persuasiveness: evidence about diagnosticity of relative actual persuasiveness. Journal of Communication 68(1), 120–142.CrossRefGoogle Scholar
Pinyol, I. & Sabater-Mir, J. 2013. Computational trust and reputation models for open multi-agent systems: a review. Artificial Intelligence Review 40(1), 1–25.CrossRefGoogle Scholar
Rahwan, I., Ramchurn, S. D., Jennings, N. R., Mcburney, P., Parsons, S. & Sonenberg, L. 2003. Argumentation-based negotiation. The Knowledge Engineering Review 18(04), 343–375.CrossRefGoogle Scholar
Ramchurn, S. D., Jennings, N. R. & Sierra, C. 2003. Persuasive negotiation for autonomous agents: a rhetorical approach. In Proceedings of the Workshop on Computational Models of Natural Argument, 9–17.Google Scholar
Ramchurn, S. D., Sierra, C., Godo, L. & Jennings, N. R. 2007. Negotiating using rewards. Artificial Intelligence 171(10–15), 805–837.CrossRefGoogle Scholar
Rienstra, T., Thimm, M. & Oren, N. 2013. Opponent models with uncertainty for strategic argumentation. In IJCAI.Google Scholar
Sabater, J. & Sierra, C. 2001. Regret: a reputation model for gregarious societies. In Proceedings of the 4th Workshop on Deception Fraud and Trust in Agent Societies, 70, 61–69.Google Scholar
Shi, B., Tao, X. & Lu, J. 2006. Rewards-based negotiation for providing context information. In Proceedings of the 4th International Workshop on Middleware for Pervasive and Ad-Hoc Computing, 8. ACM.CrossRefGoogle Scholar
Sierra, C., Jennings, N. R., Noriega, P. & Parsons, S. 1997. A framework for argumentation-based negotiation. In International Workshop on Agent Theories, Architectures, and Languages, 177–192. Springer.CrossRefGoogle Scholar
Sierra, C., Jennings, N. R., Noriega, P. & Parsons, S. 1998. A framework for argumentation-based negotiation. In Intelligent Agents IV Agent Theories, Architectures, and Languages, 177–192. Springer.CrossRefGoogle Scholar
Sycara, K. P. 1990. Persuasive argumentation in negotiation. Theory and Decision 28(3), 203–242.CrossRefGoogle Scholar
Thomas, R. J., Masthoff, J. & Oren, N. 2019. Can i influence you? development of a scale to measure perceived persuasiveness and two studies showing the use of the scale. Frontiers in Artificial Intelligence 2, 24.CrossRefGoogle Scholar
Yu, B. & Singh, M. P. 2000. A social mechanism of reputation management in electronic communities. In International Workshop on Cooperative Information Agents, 154–165. Springer.CrossRefGoogle Scholar