逐渐发展的更高层次的协同效应揭示了复杂系统中稳定性和信息整合能力之间的权衡
Thomas F Varley1,2, Josh Bongard1,2
1Department of Computer Science, University of Vermont, Burlington, Vermont 05405, USA.
Chaos (Woodbury, N.Y.)
|June 12, 2024
概括
具有高度协同作用的复杂系统是混乱的,但可以很好地整合信息. 高度冗余的系统是稳定的,但不好整合信息,揭示了稳定性和信息整合能力之间的权衡.
科学领域:
- 复杂系统科学 复杂系统科学
- 信息理论 信息理论
- 计算神经科学是一种神经科学.
背景情况:
- 新兴的组织和更高层次的结构 (协同信息) 在复杂的系统中普遍存在.
- 当前的研究往往将协同作用视为依赖变量,缺乏对其后果的统一理解.
- 在理解与不同高级结构相关的动态和信息处理能力方面存在差距.
研究的目的:
- 通过使用进化优化来演变具有显著高阶冗余,协同效应或统计复杂性的布尔网络.
- 分析这些进化的网络的动态特性和信息整合能力.
- 调查系统稳定性和信息集成之间的权衡.
主要方法:
- 进化优化,以生成有针对性的高阶属性 (冗余性,协同性,复杂性) 的布尔网络.
- 分析离散动力学,使用诸如吸引子数,平均短暂长度和德里达系数之类的指标.
- 评估系统整合信息的能力.
主要成果:
- 高协同性的网络表现为不稳定和混乱,但具有很高的信息整合能力.
- 高冗余性网络非常稳定,但信息整合能力微不足道.
- 与冗余系统相比,平衡集成和分离的复杂网络显示了中间稳定性和增强的信息集成.
结论:
- 系统的动态稳定性与其信息集成能力之间存在着根本的权衡.
- 高的协同效应导致信息整合,以牺牲稳定性.
- 复杂性,平衡整合和隔离,提供了一个中间道路,优化这种权衡.
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