SNA-based reasoning for multiagent team composition
This work addresses team composition challenges in multiagent systems, but it appears incremental as it applies existing SNA methods to a known domain without introducing major new techniques.
The paper tackled the problem of forming effective teams in multiagent systems by using social network analysis (SNA) to model agent interactions, resulting in a prototype that enables agents to adjust their social networks based on performance indicators to maximize team participation.
The social network analysis (SNA), branch of complex systems can be used in the construction of multiagent systems. This paper proposes a study of how social network analysis can assist in modeling multiagent systems, while addressing similarities and differences between the two theories. We built a prototype of multi-agent systems for resolution of tasks through the formation of teams of agents that are formed on the basis of the social network established between agents. Agents make use of performance indicators to assess when should change their social network to maximize the participation in teams