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Game algorithm of trade selection based on trust in E-marketplace

In order to solve the problem of trust management in E-marketplace where asymmetric information exists between buyers and sellers, we propose a trade selection algorithm based on game processing in C2C environment in this paper. With the idea of rational expectation of economics, the selection of rational contracting parties is imitated, and a credit-scoring model is presented according to history information about the traders, in which some speculators are removed by trade selection method. In order to make the method more effective, Swarm simulation is carried out, which tracks the trading processes and shows that how it maintain a better rate of elimination at last. The results are distinct in different scale of market, and have the benefit for the optimization of mechanism. The Swarm-based trust model in a large market is also feasible, and the reputation effect in game theory is validated here at the same time.