A multi-agent system for recommending customized families of products

Electronic markets and web-based content have improved traditional product development processes by increasing the participation of customers and applying various recommender systems to satisfy individual customer needs. This chapter introduces a multi-agent system to support customized producfamily design by recommending customers' preferences in dynamic electronic market environmentsIn the proposed system, a market-based learning mechanism is applied to determine the customerspreferences for recommending appropriate products to customers in the product family. The authors demonstrate the implementation of the proposed recommender system using a multi-agent frameworkThrough experiments, they illustrate that the proposed recommender system can determine the preference values of products for customized recommendation and market segment design in various electronic market environments.