Learning agents for dynamic supply network management
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Supply chains and supply networks rely increasingly on dynamic information flow between organisations. One problem in providing intelligent automated collaboration is incorporating learning capability i.e. an agent should be capable of adapting behaviour as conditions change. This paper proposes a scalable multi-agent system which uses case-based reasoning as a framework for part of its intelligence. Agents operate at two levels: an inter-enterprise level and a product/logistics level. Tests with a simulated system for buyer side operations show that such a buyer agent is capable of learning the best supplier and also capable of adapting if supply conditions change e.g. if average delivery times deteriorate or a new supplier enters the market.