Complexity and robustness

Highly optimized tolerance (HOT) was recently introduced as a conceptual framework to study fundamental aspects of complexity. HOT is motivated primarily by systems from biology and engineering and emphasizes, (i) highly structured, nongeneric, self-dissimilar internal configurations, and (ii) robust yet fragile external behavior. HOT claims these are the most important features of complexity and not accidents of evolution or artifices of engineering design but are inevitably intertwined and mutually reinforcing. In the spirit of this collection, our paper contrasts HOT with alternative perspectives on complexity, drawing on real-world examples and also model systems, particularly those from self-organized criticality.

[1]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[2]  S. Redner,et al.  Introduction To Percolation Theory , 2018 .

[3]  P. Bak,et al.  A deterministic critical forest fire model , 1990 .

[4]  D. Mccormick.  Normal Accidents , 1991, Bio/Technology.

[5]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[6]  Drossel,et al.  Self-organized critical forest-fire model. , 1992, Physical review letters.

[7]  D. Applebaum.  Stable non-Gaussian random processes , 1995, The Mathematical Gazette.

[8]  P. Bak,et al.  Complexity, contingency, and criticality. , 1995, Proceedings of the National Academy of Sciences of the United States of America.

[9]  M. Taqqu,et al.  Stable Non-Gaussian Random Processes : Stochastic Models with Infinite Variance , 1995 .

[10]  Per Bak,et al.  How Nature Works , 1996 .

[11]  竹中 茂夫.  G.Samorodnitsky,M.S.Taqqu:Stable non-Gaussian Random Processes--Stochastic Models with Infinite Variance , 1996 .

[12]  W. Linde.  STABLE NON‐GAUSSIAN RANDOM PROCESSES: STOCHASTIC MODELS WITH INFINITE VARIANCE , 1996 .

[13]  Azer Bestavros,et al.  Self-similarity in World Wide Web traffic: evidence and possible causes , 1997, TNET.

[14]  E. Bonabeau.  How nature works: The science of self-organized criticality (copernicus) , 1997 .

[15]  David M. Raup,et al.  How Nature Works: The Science of Self-Organized Criticality , 1997 .

[16]  D. Turcotte,et al.  Forest fires: An example of self-organized critical behavior , 1998, Science.

[17]  J M Carlson,et al.  Highly optimized tolerance: a mechanism for power laws in designed systems. , 1999, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[18]  Keeley,et al.  Reexamining fire suppression impacts on brushland fire regimes , 1999, Science.

[19]  Doyle,et al.  Highly optimized tolerance: robustness and design in complex systems , 2000, Physical review letters.

[20]  Carlson,et al.  Dynamics and changing environments in highly optimized tolerance , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[21]  Doyle,et al.  Power laws, highly optimized tolerance, and generalized source coding , 2000, Physical review letters.

[22]  Glenn Vinnicombe.  Complexity and robustness , 2000 .

[23]  J. Doyle,et al.  Robust perfect adaptation in bacterial chemotaxis through integral feedback control. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[24]  John C. Doyle,et al.  Oxygen‐mediated regulation of skeletal muscle satellite cell proliferation and adipogenesis in culture , 2001, Journal of cellular physiology.

[25]  John Doyle.  Computational biology: Beyond the spherical cow , 2001, Nature.

[26]  Jie Yu,et al.  Heavy tails, generalized coding, and optimal Web layout , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[27]  J M Carlson,et al.  Highly optimized tolerance in epidemic models incorporating local optimization and regrowth. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[28]  Temple F. Smith,et al.  Overview of the Alliance for Cellular Signaling , 2002, Nature.

[29]  Fernando Paganini,et al.  Internet congestion control , 2002 .

[30]  J. Doyle,et al.  Mutation, specialization, and hypersensitivity in highly optimized tolerance , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[31]  J. Doyle,et al.  Robustness as a measure of plausibility in models of biochemical networks. , 2002, Journal of theoretical biology.

[32]  J. Doyle,et al.  Reverse Engineering of Biological Complexity , 2002, Science.

[33]  Walter Willinger,et al.  Robustness and the Internet: Design and evolution , 2002 .

[34]  Hiroaki Kitano,et al.  The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models , 2003, Bioinform..

[35]  J. Doyle,et al.  Metabolic syndrome and robustness tradeoffs. , 2004, Diabetes.

[36]  J. Doyle,et al.  Bow Ties, Metabolism and Disease , 2022 .

[37]  Walter Willinger,et al.  A first-principles approach to understanding the internet's router-level topology , 2004, SIGCOMM '04.

[38]  Lun Li,et al.  Methodological frameworks for large-scale network analysis and design , 2004, CCRV.

[39]  Nancy Forbes,et al.  Imitation of Life: How Biology Is Inspiring Computing , 2004 .

[40]  Walter Willinger,et al.  More "normal" than normal: scaling distributions and complex systems , 2004, Proceedings of the 2004 Winter Simulation Conference, 2004..

[41]  J. Stelling,et al.  Robustness of Cellular Functions , 2004, Cell.

[42]  Bruce E. Shapiro,et al.  MathSBML: a package for manipulating SBML-based biological models , 2004, Bioinform..