GAMA (genetic algorithm driven multi-agents)for e-commerce integrative negotiation

ABSTRACT

Software agents help automate a variety of tasks including those involved in buying and selling products over the internet. The need for handling complex highly onfigurable products, together with presenting important merchant value-added services gave rise to integrative negotiation protocols. In this paper we introduce GAMA, an agent-mediated shopping system that allows shoppers to consider merchant offerings' full range of value in their buying decisions for complex products. The system helps shoppers through the two stages of product brokering and negotiation. Product Brokering is done through shopping agents adopting genetic algorithms to address the vast search space of product offerings. Integrative Negotiation is implemented using a "Collaborative GA" technique between both shopping and sales agents to satisfy the needs of both parties. The system has been simulated using the process of purchasing computers hardware. Results show that a high rate of satisfaction for both shoppers and merchants can be achieved using GAMA.

REFERENCES

• 1: R. Guttman, and P. Maes. Merchant Differentiation through Integrative Negotiation in Agent-mediated Electronic Commerce.
• 2: C. Schmitt, D. Dengler, M. Bauer. The MAUT Machine: An Adaptive Recommender System. Springer Berlin/Heidelberg, Volume 2702/2003
• 3: John R. Koza. Genetic Programming. MIT Press, 1996

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.6 SIMULATION AND MODELING
      I.6.m Miscellaneous

Additional Classification:
  J. Computer Applications
  J.m MISCELLANEOUS

General Terms:
Algorithms

Keywords:
e-commerce, genetic algorithms, multi-agents, multi-attribute