Simulation-based Approach to Evaluate and Regulate the Reputation Score of a Software Agent in E-Market

Reputation is a crucial factor that governs the importance of a software agent in the agent-mediated e-market. In the e-market, various buyers and service providers are involved in buying and selling the products. A buyer agent (BA) acts on behalf of a buyer to buy the products from a service provider agent (SPA) preferably having a good reputation score (Rep-Score). The conventional customer rating mechanism for online transactions lacks adequate analysis and investigation of customer reviews and hence does not reflect the accurate reputation of the service providers. This research investigates the reputation of a software agent using customer feedback based on product attributes such as product quality, design, price, delivery time, and defects. A knowledge rule-set is formed to establish a link between customer feedback and the repute of a software agent. Further, a simulation-based approach using the Rosetta toolkit and the Fuzzy Control System is applied to quantify and fine-tune the reputation of a software agent. There could be a chance of an unfair relationship between the same buyer-seller pair due to recurrent transactions. The proposed work eliminates any chance of a conspiracy between a service provider and a buyer agent. In case, the buyer agent makes repeated transactions with a particular service provider agent, the value of the weight assigned to the reputation of the service provider agent is significantly diminished for each new transaction, hence decreasing the final value of the Rep-Score. As a result, this method guarantees the correctness of the reputation evaluation of a software agent. A performance analysis is performed to validate the proposed approach using mean squared error and standard deviation.