Complexity and robustness

By Jean M. Carlson, John C. Doyle. Proceedings of the National Academy of Sciences of the United States of America, 2001

858 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Economics and Econometrics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/000d9e2903764f9a6c173ce5ab3b43faabbc69cc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

In Economics and Econometrics

In Statistical and Nonlinear Physics

Citations in the corpus

Towards a theory of biological robustness (2007, methodology): “This figure is inspired by the HOT theory (Carlson and Doyle, 1999, 2002).”
Robustness of Cellular Functions (2004, neutral): “…shielding leads to higher complexity and new potenally different entities perform overlapping functions, which tial sources of fragility (Carlson and Doyle, 2002). lead to the suggestion to use " degeneracy " as a more Cancer offers an intuitive illustration for these conappropriate…”
Network resilience (2020, background): “about technical complex networks, including CI, analyze them from the point of view of complexity science [571, 572, 573, 41, 574].”
Indicators for Complex Innovation Systems (2006, background): “Power laws are common to physical (Christensen et al., 2002; Warhaft 2002), natural science (Goldberger et al., 2002; Katz et al., 1999; West et al., 2002) and social systems (M. E. J. Newman et al., 2002).”
Statistical properties of community structure in large social and information networks (2008, background): “This model is also different than generative models such as preferential attachment models [9, 124, 25] or models based on optimization [56, 57, 60], although common to all of these generative models is that they attempt to reproduce empirically-observed power-law behavior [11, 61, 27, 126, 49].”
Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters (2008, background): “This model is also different than generative models such as preferential attachment models [9, 127, 25] or models based on optimization [57, 58, 61], although common to all of these generative models is that they attempt to reproduce empirically-observed power-law behavior [11, 62, 27, 129, 50].”
Resilience and robustness in policy design: a critical appraisal (2017, background): “…resilience, which is the ability to maintain functions and control in the presence of external disturbance (Jen 2003) and ‘the maintenance of some desired system characteristics despite fluctuations in the behaviour of its component parts or its environment’ (Carlson and Doyle 2002, p. 2538).”
Geometric Programming for Communication Systems (2005, background): “It is argued in [49, 27] that many mechanisms in complex systems are implicitly solving a PLR problem with different β, c,p, R constants.”
Towards a Theory of Scale-Free Graphs: Definition, Properties, and Implications (2005, methodology): “Speciﬁcally, the notions of Highly Optimized Toler-ance (HOT) [27] or Heuristically Organized Tradeoffs [40] has been recently introduced as a conceptual framework for capturing the highly organized, optimized, and “robust yet fragile” structure of complex highly evolved systems [28].”
Robustness Trade-offs in Social-Ecological Systems (2007, background): “Given such perturbations, the capacity to maintain system performance when subjected to external or internal unpredictable perturbations (Carlson and Doyle 2002), can be of critical importance in SESs.”
On the Definition of Cyber-Physical Resilience in Power Systems (2015, background): “The more an infrastructure network is designed to be robust against one set of disturbances, the more fragile it is when faced with a different set of disturbances [49].”
Considering complexity in healthcare systems (2011, background): “This ability of complex systems to maintain certain characteristics despite environmental influences, often termed robustness [4], has inspired the resilience engineering approach [14], which aims to improve the ability of error-critical systems, including the healthcare system, to tolerate human er”
A Framework to Analyze the Robustness of Social-ecological Systems from an Institutional Perspective (2004, background): “The concept of robustness is well developed in engineering where it refers to the maintenance of system performance either when subjected to external, unpredictable perturbations, or when there is uncertainty about the values of internal design parameters (Carlson and Doyle, 2002).”