通过综合信息分解来实现信息动态的统一分类
Pedro A M Mediano1,2, Fernando E Rosas3,4,5,6, Andrea I Luppi6,7,8
1Department of Computing, Imperial College London, London SW7 2AZ, United Kingdom.
概括
我们介绍了综合信息分解 (IID),这是一个新的数学框架来量化复杂的系统相互作用. 国际信息发展 (IID) 增强了对信息流和各种科学领域的动态复杂性的理解.
科学领域:
- 复杂系统科学 复杂系统科学
- 信息理论 信息理论
- 数学建模的数学建模
背景情况:
- 了解和控制复杂的系统,其中有许多相互影响的部分是具有挑战性的.
- 量化这些系统内的多对多的动态相互作用仍然是一个关键的局限性.
研究的目的:
- 介绍综合信息分解 (IID) 作为一个数学框架.
- 提供一种全面的方法来解和描述复杂的多变量系统中的信息动态.
- 克服现有信息传输,存储和复杂性措施的理论缺陷.
主要方法:
- 开发了综合信息分解 (IID) 的理论框架.
- 识别和描述了集体信息流的新模式.
- 使用计算模型和来自1000多个不同的动态系统的经验数据验证了IID.
主要成果:
- IID揭示了以前没有报道的集体信息流的模式.
- 现有的信息传输,存储和复杂性的措施可以用这些模式的总和来表达.
- 证明了IID在生物,社会,物理和合成系统中的适用性和有效性.
结论:
- IID显著提高了对广泛用于描述复杂系统的测量方法的理解.
- 该框架允许对动态复杂性的更精细的分析.
- IID为研究跨多学科复杂系统提供了一个强大的新工具.
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