Constrained Coalition Formation among Heterogeneous Agents for the Multi-Agent Programming Contest

This work focuses on coalition formation among heterogeneous agents for a simulated scenario involving logistic and coordination problems. We investigate whether organising a team of agents into a number of coalitions, in which agents collaborate with each other to achieve particular goals, can increase the effectiveness of the team. We apply coalition structure generation specifically to the 2017 multi-agent programming contest, where the agents controlling various autonomous vehicles form a competing team that has to solve logistic problems simulated on the map of a real city. We experiment on three approaches with different configurations. The first uses only a task-allocation mechanism, while the other approaches use either an optimal or a heuristic coalition formation algorithm. Our results show that coalition formation can improve the performance of a participating team under some circumstances. In particular, coalition formation can indeed play an important role when we aim to balance the skills in groups of agents selected to accomplish some given set of tasks given a larger team of cooperating agents in the presence of dynamically created tasks.