Optimizing One-to-Many Negotiation Agents in E-Commerce Using Aspiration Concept

With the growth of World Wide Web and increasing human demand on trading, e-commerce becomes an inseparable part of business. In the past decade a huge number of researches have been done in order to develop optimal negotiation agent systems in e-commerce. However, existing models are weak in supporting real world e-market conditions since most of them assume static conditions for environment and complete information about opponent agent's preferences. As a result, this work proposes an adaptive one-to-many negotiation model called Aspiration negotiation model. This model is proposed in order to assist agents to adapt to the dynamicity of opponent agent's preferences and environmental conditions. Proposed model is employed in order to optimize the negotiation outcome in terms of utility gained by agents. Experimental studies have been done to evaluate the performance of proposed model. Finally Aspiration model was able to outperform previous models in terms of seller, buyer and joint utility value.