Abstract
Industrial clusters are complex networks formed by numerous agents who continuously imitate, learn from each other and make optimal choice accordingly. The paper uses random learning game and multi-agent system models to construct a Chinese traditional industrial clusters low carbon evolution model and introduce an algorithm based on the network external effect and characteristics of agents adaptive behavior. Then the simulation of low-carbon competition, emergence and evolution was conducted, which produced some valuable conclusions.
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