  Traditionally, researchers in decision making have focused on attempting to
reach Pareto Optimality using horizontal approaches, where optimality is
calculated taking into account every participant at the same time. Sometimes,
this may prove to be a difficult task (e.g., conflict, mistrust, no information
sharing, etc.). In this paper, we explore the possibility of achieving Pareto
Optimal outcomes in a group by using a bottom-up approach: discovering Pareto
optimal outcomes by interacting in subgroups. We analytically show that Pareto
optimal outcomes in a subgroup are also Pareto optimal in a supergroup of those
agents in the case of strict, transitive, and complete preferences. Then, we
empirically analyze the prospective usability and practicality of bottom-up
approaches in a variety of decision making domains.
