A collection of agents, faced with multiple tasks to perform, must effectively map agents to tasks in order to perform the tasks quickly with limited wasted resources. We propose a decentralized control algorithm based on synchronized random number generators to enact a cooperative task auction among the agents. The algorithm finds probabilistically reasonable solutions in a few rounds of bidding. Additionally, as the length of the auction increases, the expectation of a tener solution increases. This algorithm is not intended to find the optimal solution; it finds a "'goad" solution with less computation and communication.
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