Abstract
The paper describes the design, implementation and user evaluation of utility and goal-based intelligent learning agents for smart shopping cart. In keeping user’s shopping habits rules and shopping list, they guide visitors through the shops and the goods in the shopping center or according to new promotions in the shops, respectively. It is envisaged that concrete implementation of the shopping agents will be running on each shopping cart in the shopping centers. The k-d decision tree, the smallest identification tree and reinforcement-learning algorithm are used for agents learning. Some initial user opinions of the shopping cart agents are presented.
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