Group Role Assignment with Agents' Preferences

Abstract

Using the Role-Based Collaboration (RBC) methodology that advocates collectivism and the Environments - Classes, Agents, Roles, Groups, and Objects (E-CARGO) model, this paper formalizes the problem of considering individual preferences in a group with the support of Group Role Assignment (GRA); analyzes the impact of agents' preferences on group performance through simulations. The contributions of this work include: 1) formalization of the proposed problem, i.e. GRA with Agents' Preferences (GRAAP); 2) a practical solution to the problem, i.e., GRA with Integrated Agents' Preferences (GRAIAP); 3) benefit verification through simulations; and 4) a conclusion that can be applied to industries requiring collaborative effort.