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Building coalitions of heterogeneous agents using weighted bipartite graphs

Abstract:

Teams of agents with different skills can solve critical missions by efficiently joining their complementary abilities. One critical step to exploit the distinct resources available on a set of agents is to form a coalition, i.e., an alliance that satisfies the requirements imposed by a mission. In this work, we represent the relation between agent capabilities and required resources for executing a given task by a weighted bipartite graph. Using this graph, we find an assignment between agents and resource capabilities such that the total weight of capabilities is maximized. From this assignment, also known as matching in Graph Theory, we compute a coalition of agents whose total resource capabilities can satisfy the task resource requirements. Finally, we measure the heterogeneity of the computed coalition and analyze how it is affected by the task constraints and the amount of resources present in the agents.