Multi Agent System Based on E-trading Strategy Using Machine Learning

Present study analyzes the state of the art of autonomous software agents represents modern e-commerce concentrating particularly on the business-to-consumer (B2C) and business-tobusiness (B2B) aspects. Currently, however, most applications are either B2C or B2B and, therefore, these are the two applications that we focus on here according to agent prospective. MAS model has been extensively used in the different tasks of adoption of e-commerce such as negotiation in B2B or B2C in proposed method. By increasing the degree and the sophistication of the automation, on either the buyer’s or contractee and the seller’s or contractor, not only to enhance the benefit, but also presented that the application of this analysis to the task allocation domain in a cooperative MAS. The contractee agent first evaluates the index of negotiation value of the various contractor agents and then selects that contractor’s bid for negotiation that has better index of negotiation value. A GUI and tabular result to show the mechanism in proposed method. KeywordsMulti agent, B2B, B2C, Negotiation, Brokering ,Trust