通过联来表征高阶的相互依赖
Fernando E Rosas1,2,3,4, Aaron J Gutknecht5, Pedro A M Mediano6,7
1Sussex AI and Sussex Centre for Consciousness Science, Department of Informatics, University of Sussex, Brighton, UK.
概括
我们将介绍联, 这是一个理解复杂系统中高阶依赖关系的新原理. 这一框架阐明了现有的措施,并将O信息确定为分析系统相互作用的关键工具.
科学领域:
- 复杂系统科学
- 信息理论
- 统计物理
背景情况:
- 高阶现象在复杂系统中很常见,但很难正式描述.
- 现有的信息理论衡量高阶相互依赖性缺乏明确的概念基础和关系.
- 这种模糊性阻碍了适合应用的分析工具的选择.
研究的目的:
- 作为研究高阶测量的一种正式原则, 引入化结合.
- 澄清现有的高阶依赖措施的性质和关系.
- 确定当前关于量化复杂系统相互作用的文献上的差距.
主要方法:
- 正式介绍了结原理.
- 信息理论数量的对称性和斜对称性属性的分析.
- 对系统大小的高阶措施的估计成本扩展的调查.
主要成果:
- 输入组合为高阶测量提供了一个统一的框架.
- 该原则揭示了缺陷,并澄清了现有措施的性质.
- O-信息被确定为具有线性估计成本的独特对称度量.
结论:
- 输入式结合为分析高阶相互依赖提供了一个原则性的方法.
- 对称性和斜对称性是平衡分析的关键指标.
- 对复杂的系统而言,O信息是一个自然而有效的措施.
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