Research On Multi-Agent Based Simulation Application In Game Theory

In recent years, along with the development of computer science, economic simulation receives the economist's attention more and more as the new method of economics research. It may imitate and show various conditions of economical operation, give suggestion and reference information accordingly. Swarm is the example with representatives. It has been used to do economic simulation researches on many fields. Firstly, the author presents domestic and international development trends of the game theory as one of the mainstreams in current economics in this article. On the basis of which, by combining Swarm artificial technology based on multi-agent, have solved the limitation in dynamic analysis of game theory. Swarm artificial technology as a bottom-up simulation method utilizes the latest research results of artificial intelligence and computer science domain, builds agents on micro level and aggregates the behavior to macro level. Meanwhile, the author introduces nowadays popular multi-agent based simulation technologies, and has analyzed its one's own application characteristics, suitable field. Secondly, using the game theory analytical method, the author structures the dynamic model at random of nonlinearity that a counterfeit supply under market condition. Then with the aid of Swarm simulation, according to oriented object program design, use Objective-C programming language to realize the dynamic simulation of the dynamic model at random of nonlinearity that above-mentioned counterfeit supply, and has carried on a large number of data experiments on Swarm artificial platform. The artificial result indicate that this model can portray out the course of advancing gradually dynamically of the non-linear random model more accurately. Finally, the author summarized that the Swarm advance, superiority, suitability in the simulation application of game theory, and believe that the Swarm has wide application prospect. Meanwhile, the author makes propose to weak point in the development and problem that need to solve further in Swarm.