In this article, we introduce a new paradigm to achieve Pareto optimality in group decision-making processes: bottom-up approaches to Pareto optimality. It is based on the idea that, while resolving a conflict in a group, individuals may trust some members more than others; thus, they may be willing to cooperate and share more information with those members. Therefore, one can divide the group into subgroups where more cooperative mechanisms can be formed to reach Pareto optimal outcomes. This is the first work that studies such use of a bottom-up approach to achieve Pareto optimality in conflict resolution in groups. First, we prove that an outcome that is Pareto optimal for subgroups is also Pareto optimal for the group as a whole. Then, we empirically analyze the appropriate conditions and achievable performance when applying bottom-up approaches under a wide variety of scenarios based on real-life datasets. The results show that bottom-up approaches are a viable mechanism to achieve Pareto optimality with applications to group decision-making, negotiation teams, and decision making in open environments.
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Keywords Agreement technologies, Automated negotiation, Group decision making, Multi-agent systems, Pareto optimality
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Journal Knowledge and Information Systems
Project Representing Users in a Negotiation (RUN): An Autonomous Negotiator Under Preference Uncertainty
Grant This work was funded by the The Netherlands Organisation for Scientific Research (NWO); grant id nwo/639.021.751 - Representing Users in a Negotiation (RUN): An Autonomous Negotiator Under Preference Uncertainty
Sanchez-Anguix, V, Aydoğan, R, Baarslag, T, & Jonker, C.M. (2019). Bottom-up approaches to achieve Pareto optimal agreements in group decision making. Knowledge and Information Systems, 1–28. doi:10.1007/s10115-018-01325-y