Human civilization dynamics: why we have different civilization patterns in history.

After the Axial Age, the West moved toward continuous disunity, but China had successfully maintained a persistent unity pattern. Conventional case (history event) studies are subject to selection bias and theoretical frameworks, which is not objective narrative. We use agent-based modeling (ABM) to reveal the historical dynamics of why civilizations take on distinct patterns (unity versus disunity). In China, the Qin Dynasty (initial unity) opened the Great Unity tradition in 221 BC. Before this, there was a major chaotic period (770 BC to 221 BC) with two periods. The first period, the Spring and Autumn (770 BC to 221 BC), opened this chaotic process and indirectly led to the initial unity. Then, the second period, the Warring States period (475 BC to 221 BC), directly led to this initial unity. This work models the second period and focuses on the question of why human civilizations take on different patterns in history. Finally, we have solved the conditions and boundaries of two patterns. Based on the second period, we have different conclusions. The bellicosity threshold is around 0.2 (for the previous period, this is 0.3), and the alliance propensity threshold is around 0.8 (for the previous period, this is 0.7). Moreover, the higher winner cost (beyond 5%) makes it impossible to achieve Unity. This work has one new contribution, such as solving social knowledge. We use BP neural networks to evaluate the knowledge graph to support history learning. It explains civilization patterns for humankind. [ABSTRACT FROM AUTHOR]

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