A multi-agent model for cooperation and negotiation in supply networks
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Automation of inter-organizational cooperation and negotiation in supply networks with dynamic information flow needs intelligent software with a capacity for adaptation. The aim of this paper is to propose a multi-agent architecture for cooperation and negotiation in supply networks (MCNSN), which incorporates a learning capability for agents, and discusses the issues which need to be addressed for coordination of buyers and sellers, both at a transaction and an organizational level, as well as the broader issues of cooperation and negotiation. Certain agents use case-based reasoning (CBR) as a framework for learning the best strategy between buyers and suppliers. MCNSN operates at two levels. The first is a transaction/enterprise level which requires dynamic customer relationship management (CRM) information, user profiling and will eventually need a bargaining capability. The second is at a logistics/manufacturing level which deals with product transfer and requires learning cost-effective buyer/supplier dealings for specific products.