Many multi-agent systems consist of a complex network of autonomous yet interdependent agents. Examples of such networked multi-agent systems include supply chains and sensor networks. In these systems, agents have a select set of other agents with whom they interact based on environmental knowledge, cognitive capabilities, resource limitations, and communications constraints. Previous findings have demonstrated that the structure of the artificial social network governing the agent interactions is strongly correlated with organizational performance. As multi-agent systems are typically embedded in dynamic environments, we wish to develop distributed, on-line network adaptation mechanisms for discovering effective network structures. Therefore, within the context of dynamic team formation, we propose several strategies for agentorganized networks (AONs) and evaluate their effectiveness for increasing organizational performance.
Team Formation: Initially, the team formation problem is studied in the multi-agent systems REF , which are typically embedded in dynamic environments.
Agent-organized networks for dynamic team formation
AAMAS '05
Computer Science