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A computational science approach to understanding human conflict

机译:理解人类冲突的计算科学方法

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We discuss how computational data science and agent-based modeling, are shedding new light on the age-old issue of human conflict. While social science approaches focus on individual cases, the recent proliferation of empirical data and complex systems thinking has opened up a computational approach based on identifying common statistical patterns and building generative but minimal agent-based mod els. We discuss a reconciliation for various disparate claims and results in the literature that stand in the way of a unified description and understanding of human wars and conflicts. We also discuss the unified interpretation of the origin of these power-law deviations in terms of dynamical processes. These findings show that a unified computational science framework can be used to understand and quantitatively describe collective human conflict. (c) 2020 Elsevier B.V. All rights reserved.
机译:我们讨论了计算数据科学和基于代理的建模如何,正在对人类冲突的古老阶段发出新的光线。虽然社会科学方法关注个人案例,但最近的经验数据和复杂系统思维的扩散已经基于识别常见的统计模式和建筑工成的基于代理的MOD ELS来开辟了一种计算方法。我们讨论对各种偏差索赔的和解,并在统一描述和对人类战争和冲突的理解方面取得的文献。我们还讨论了在动态过程方面对这些权力律偏差起源的统一解释。这些调查结果表明,统一的计算科学框架可用于理解和定量描述集体人类冲突。 (c)2020 Elsevier B.v.保留所有权利。

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