Distributed Multi-Agent Hierarchy Construction for Dynamic DCOPs in Mobile Sensor Teams

Abstract

Coordinating multiple agents to optimize an objective has several real-world applications. In areas such as disaster rescue, environment monitoring and the like, mobile agents may be deployed to work as a team to achieve a joint goal. Recently, multi-agent problems involving mobile sensor teams have been formalized in the literature as DCOP_MSTs. Under this class of problems, DCOP algorithms are applied to enable agents to coordinate the assignment of their physical locations as they jointly optimize the team objective. In DCOP_MSTs, the environment is dynamic, and agents may leave or join the environment at random times. As a result, a predefined interaction topology or graph may not be useful over the problem horizon. Therefore, there is a need to study methods that could facilitate agent-to-agent interaction in such open and dynamic environments. Existing methods require reconstructing the entire graph upon detecting changes in the environment or assume a predefined interaction graph. In this study, we propose a dynamic multi-agent hierarchy construction algorithm that can be used by DCOP_MST algorithms that require a pseudo-tree for execution. We evaluate our proposed method in a simulated target detection case study to show the effectiveness of the proposed approach in large agent teams.