汇集理论及其与计算复杂性的关系
Christopher P Kempes1, Michael Lachmann1,2, Andrew Iannaccone3
1The Santa Fe Institute, Santa Fe, NM USA.
概括
装配理论 (AT) 使用装配指数量化复杂性,测量构建对象所需的因果步骤. 这种方法将选择驱动的复杂性与随机生成区分开来,提供了一个物理可测量的框架.
科学领域:
- 物理 物理学 物理
- 信息理论 信息理论
- 理论生物学 理论生物学
背景情况:
- 选择是推动自然复杂性的关键机制.
- 现有的复杂性测量通常侧重于可压缩性,而不是因果史.
- 需要一个物理可测量的复杂性框架.
研究的目的:
- 引入装配理论 (AT) 作为一种用于量化复杂性的新框架.
- 为了区分AT与传统的计算复杂性和压缩算法.
- 为了建立AT的基础在可测量的物理因果关系中.
主要方法:
- 使用汇编索引和副本编号开发了汇编方程.
- 制定了数学示例来说明区别.
- 提供了计算复杂度类的理论证明.
主要成果:
- 组装指数量化因果步骤,与可压缩性指标不同 (例如,香农,LZW).
- 组装指数属于不同的计算复杂度类比压缩算法.
- 装配理论提供了一种物理可测量的复杂性方法.
结论:
- 集合理论提供了一种新的方法来量化基于因果历史和选择的复杂性.
- 复杂度测量提供了一个强大的,有经验基础的替代方案,而不是抽象的复杂度测量.
- 这一框架对理解复杂系统,包括生命,有影响.
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