Abstract
Supporting group decision-making is a complex process, especially when decision-makers have no opportunity to gather at the same place and at the same time. Besides that, finding solutions may be difficult in case representing agents are not able to understand the process and support the decision-maker accordingly. Here we propose a model and an algorithm that will allow the agent to analyse tendencies. This way we intend that agents can achieve decisions with more quality and with higher levels of consensus. Our model allows the agent to redefine his objectives to maximize both his and group satisfaction. Our model proved that agents that use it will obtain higher average levels of consensus and satisfaction. Besides that, agents using this model will obtain those higher levels of consensus and satisfaction in most of the times compared to agents that do not use it.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Luthans, F.: Organizational Behavior. McGraw-Hill, Boston (2005)
DeSanctis, G., Gallupe, B.: Group decision support systems: a new frontier. ACM SIGMIS Database 16, 3–10 (1984)
Desanctis, G., Gallupe, R.B.: A foundation for the study of group decision support systems. Manage. Sci. 33, 589–609 (1987)
Grudin, J.: Group dynamics and ubiquitous computing. Commun. ACM 45, 74–78 (2002)
Marreiros, G., Santos, R., Ramos, C., Neves, J.: Context-aware emotion-based model for group decision making. IEEE Intell. Syst. 25, 31–39 (2010)
Carneiro, J., Santos, R., Marreiros, G., Novais, P.: UbiGDSS: a theoretical model to predict decision-makers’ satisfaction. Int. J. Multimed. Ubiquit. Eng. 10, 191–200 (2015)
Kwon, O., Yoo, K., Suh, E.: UbiDSS: a proactive intelligent decision support system as an expert system deploying ubiquitous computing technologies. Expert Syst. Appl. 28, 149–161 (2005)
Shim, J.P., Warkentin, M., Courtney, J.F., Power, D.J., Sharda, R., Carlsson, C.: Past, present, and future of decision support technology. Decis. Support Syst. 33, 111–126 (2002)
Paul, S., Seetharaman, P., Ramamurthy, K.: User satisfaction with system, decision process, and outcome in GDSS based meeting: an experimental investigation. In: Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS 2004)-Track 1, vol. 1, pp. 10037–10032. IEEE Computer Society (2004)
Carneiro, J., Marreiros, G., Novais, P.: Using satisfaction analysis to predict decision quality. Int. J. Artif. Intell.™ 13, 45–57 (2015)
Muller, J., Hunter, A.: An argumentation-based approach for decision making. In: 2012 IEEE 24th International Conference on Tools with Artificial Intelligence (ICTAI), pp. 564–571. IEEE (2012)
Marey, O., Bentahar, J., Khosrowshahi-Asl, E., Sultan, K., Dssouli, R.: Decision making under subjective uncertainty in argumentation-based agent negotiation. J. Ambient Intell. Humanized Comput. 6, 307–323 (2015)
Dennis, A.R.: Information exchange and use in small group decision making. Small Group Res. 27, 532–550 (1996)
Hill, G.W.: Group versus individual performance: are N + 1 heads better than one? Psychol. Bull. 91, 517 (1982)
Higgins, E.T.: Making a good decision: value from fit. Am. Psychol. 55, 1217 (2000)
Schimmack, U., Oishi, S., Furr, R.M., Funder, D.C.: Personality and life satisfaction: a facet-level analysis. Pers. Soc. Psychol. Bull. 30, 1062–1075 (2004)
Judge, T.A., Heller, D., Mount, M.K.: Five-factor model of personality and job satisfaction: a meta-analysis. J. Appl. Psychol. 87, 530 (2002)
Ramchurn, S.D., Jennings, N.R., Sierra, C.: Persuasive negotiation for autonomous agents: a rhetorical approach (2003)
Ito, T., Shintani, T.: Persuasion among agents: an approach to implementing a group decision support system based on multi-agent negotiation. In: International Joint Conference on Artificial Intelligence, pp. 592–599. Citeseer (1997)
Kraus, S., Sycara, K., Evenchik, A.: Reaching agreements through argumentation: a logical model and implementation. Artif. Intell. 104, 1–69 (1998)
Martinho, D., Carneiro, J., Marreiros, G., Novais, P.: Dealing with Agents’ Behaviour in the Decision-Making Process. In: SOOW (2015)
Acknowledgements
This work has been supported by COMPETE Programme (operational programme for competitiveness) within project POCI-01-0145-FEDER-007043, by National Funds through the FCT– Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within the Projects UID/CEC/00319/2013, UID/EEA/00760/2013, and the João Carneiro PhD grant with the reference SFRH/BD/89697/2012 and by Project MANTIS - Cyber Physical System Based Proactive Collaborative Maintenance (ECSEL JU Grant nr. 662189).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Carneiro, J., Martinho, D., Marreiros, G., Novais, P. (2016). The Effect of Decision Satisfaction Prediction in Argumentation-Based Negotiation. In: Bajo, J., et al. Highlights of Practical Applications of Scalable Multi-Agent Systems. The PAAMS Collection. PAAMS 2016. Communications in Computer and Information Science, vol 616. Springer, Cham. https://doi.org/10.1007/978-3-319-39387-2_22
Download citation
DOI: https://doi.org/10.1007/978-3-319-39387-2_22
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-39386-5
Online ISBN: 978-3-319-39387-2
eBook Packages: Computer ScienceComputer Science (R0)