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This paper applies the multi-agent system Strategy to collaborative negotiation in manufacturing supply chain coordination. Multi-agent computational environments are suitable for studying a broad class of coordination and negotiation issues involving multiple autonomous or semiautonomous problem solving agents.
With the trend of globalization, increased customer demand and advancement in technology development, firms are experiencing ever intense pressure to collaborate with their trading partners to compete with other supply chains. Firms are seeking to collaborate with their partners at greater extent in the areas such as knowledge management to exploit the potentials of an efficient and effective supply...
Collaborative filtering recommendation algorithm has proved to be one of the most successful algorithms in recommender systems in recent years. However, traditional centralized collaborative filtering system has suffered from its shortage in scalability as their calculation complexity increases quickly both in time and space when the number of the user and item in the rating database increases. As...
Recommender systems represent personalized services that aim at predicting userspsila interest on information items available in the application domain. Collaborative filtering technique has been proved to be one of the most successful techniques in recommendation systems in recent years. Poor quality is one major challenge in collaborative filtering recommender systems. Sparsity of userspsila ratings...
This paper proposes a cooperation mechanism among seller agents and builds a model based on multi-agent system. In the model, a manger agent has been set to watch activities of other agents. It will encourage the cooperative sellers and punish the non-cooperative seller agents by adjust the sellerpsilas reputation in the repository. With this mechanism, a seller would complete the trade with the buyer...
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