We propose an efficient team formation method for multi-agent systems consisting of self-interested agents in task-oriented domains. Services computing on computer networks have been rapidly increasing. Efficient team formation for service tasks is considered to be a way to improve performance. Our method is based on our previous parameter learning method enabling agents to efficiently form teams but requiring prior knowledge about all others' resources. We extended that method by adding a resource estimation method so as to increase its applicability to actual application systems. We experimentally evaluated our method by comparing it with the previous method and the task allocation using contract net protocol (CNP). The results demonstrated that the proposed method outperformed other methods even though it did not require prior knowledge about resources in other agents. We discuss the reason for this improvement.
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