Opinion evolution based on cellular automata rules in small world networks

doi:10.1088/1674-1056/19/3/038701

Abstract In this paper, we apply cellular automata rules, which can be given by a truth table, to human memory. We design each memory as a tracking survey mode that keeps the most recent three opinions. Each cellular automata rule, as a personal mechanism, gives the final ruling in one time period based on the data stored in one's memory. The key focus of the paper is to research the evolution of people's attitudes to the same question. Based on a great deal of empirical observations from computer simulations, all the rules can be classified into 20 groups. We highlight the fact that the phenomenon shown by some rules belonging to the same group will be altered within several steps by other rules in different groups. It is truly amazing that, compared with the last hundreds of presidential voting in America, the eras of important events in America's history coincide with the simulation results obtained by our model.

Keywords: cellular automata rules truth table memory simulation

Received: 27 March 2009
Revised: 23 August 2009
Accepted manuscript online:

PACS:	87.18.Sn	(Neural networks and synaptic communication)
	87.10.-e	(General theory and mathematical aspects)

Cite this article:

Shi Xiao-Ming(石晓明), Shi Lun(施伦), and Zhang Jie-Fang(张解放) Opinion evolution based on cellular automata rules in small world networks 2010 Chin. Phys. B 19 038701

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Opinion evolution based on cellular automata rules in small world networks

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