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Token-based autonomous task allocation in flocking systems

There are serious contributions to the theoretical foundations of flocking systems, but there are only few systems which have the capability of autonomous task allocation, however, many use cases demand this functionality. The implementation of a task allocation algorithm could be a serious challenge even in a simulated environment due to the numerous problems arising from the nature of these systems. This paper proposes a novel algorithm to find the optimal allocation of heterogeneous agents to heterogeneous tasks by utilizing distributed auctions based on local peer-to-peer wireless communication and exploiting graph theory with a tree-based multicast protocol. The solution was tested over a number of different scenarios and compared to existing algorithms in order to measure and prove its capability in handling autonomous task allocation in different systems as well.