Multi Agent Based System to Automate Shopping Process Using Artificial Intelligence

First system can acquire the customer’s current needs from System customer interactions. Then system combines expert knowledge and customer’s current needs, and recommends optimal products based on multi-attribute decision method. If we want to maintain semantic conversation with sellers, commodity ontology is also utilized to support sharable information format and the representation. Agent methodology is-to support Ecommerce operations in the project like automating buying and selling process is promising and worth of success. The work process proposed in our paper aiming to present minimum solutions to increase and facilitate e- commerce transactions including automated price negotiations. It is a system, where users can assign their tasks to agents, which will do shopping job on their behalf and present them results. It shows how these requirements are used to develop the multi agent-based simulation prototype of customer's shopping behavior in mall. Mainly the agents are assigned with special features and capabilities, this prototype can consider sufficiently believable and usable for end-users, mainly the mall managers. We show how shopping behavior simulator can support decision making process with respect to spatial configuration of shopping mall.