Simulating collective behaviors of human groups with interactions has essential importance in education, economics, psychology and other social science fields. In this paper, we gave a cellular automata based method to analyze group learning behavior. The paper analyzed the interaction relationship between individual behavior and group evolvement, and discussed how the evolvement of group is affected by qualified rate in initial condition, the interaction level and distribution of individuals in the sense of statistics. A large number of experiments are employed to show how some main factors effect the group evolvement and to draw related conclusions.
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