Multi Agent Based System to Automate Shopping Process Using Artificial Intelligence
Abstract
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.
Country : India
1 Santhosh Kumar Potnuru
Associate Professor, Department of Computer Science and Engineering, Malla Reddy College of Engineering for Women, Hyderabad -500100, Telangana, India
