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Life is not on the edge of chaos but in a half-chaos of not fully random systems. Definition and simulations of the half-chaos in complex networks
Adaptation and Self-Organizing Systems · Submitted 27 Dec 2017
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim It gives a base for identity criterion of an evolving object, simplifies the definition of basic Darwinian mechanism and changes "life on the edge of chaos" to "life evolves in the half-chaos of not fully random systems".
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The research concerns the dynamics of complex autonomous Kauffman networks. The article defines and shows using simulation experiments half-chaotic networks, which exhibit features much more similar to typically modeled systems like a living, technological or social than fully random Kauffman networks. This makes a large change of widely taken view in the dynamics of complex networks. Current theory predicts that random autonomous systems can be either ordered or chaotic with fast phase transition between them. However, modeled adapted systems are not fully random, they are usually stable, but the estimated parameters are usually "chaotic", they place the fully random networks in the chaotic regime, far from the narrow phase transition. It is showed that among the not fully random systems with "chaotic parameters", a large third state called half-chaos exists, which simultaneously exhibit small (ordered) and large (chaotic) reactions for small disturbances in similar share. The discovery of half-chaos frees modeling of adapted systems from sharp restrictions; it allows to use "chaotic parameters" and get a nearly stable system more similar to modeled one. It gives a base for identity criterion of an evolving object, simplifies the definition of basic Darwinian mechanism and changes "life on the edge of chaos" to "life evolves in the half-chaos of not fully random systems".
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | The research concerns the dynamics of complex autonomous Kauffman networks. | background 0.77 | 0.51 | 0.02 | asserted 0.78 |
| s1 | The article defines and shows using simulation experiments half-chaotic networks, which exhibit features much more similar to typically modeled systems like a living, technological or social than fully random Kauffman networks. | contribution 0.93 | 0.94 | 0.39 | asserted 1.00 |
| s2 | This makes a large change of widely taken view in the dynamics of complex networks. | interpretation 0.96 | 0.38 | 0.15 | asserted 0.99 |
| s3 | Current theory predicts that random autonomous systems can be either ordered or chaotic with fast phase transition between them. | background 1.00 | 0.04 | 0.03 | asserted 0.99 |
| s4 | However, modeled adapted systems are not fully random, they are usually stable, but the estimated parameters are usually "chaotic", they place the fully random networks in the chaotic regime, far from the narrow phase transition. | background 0.65 | 0.17 | 0.07 | asserted 0.90 |
| s5 | It is showed that among the not fully random systems with "chaotic parameters", a large third state called half-chaos exists, which simultaneously exhibit small (ordered) and large (chaotic) reactions for small disturbances in similar share. | result 0.99 | 0.92 | 0.52 | asserted 1.00 |
| s6 | The discovery of half-chaos frees modeling of adapted systems from sharp restrictions; it allows to use "chaotic parameters" and get a nearly stable system more similar to modeled one. | interpretation 0.98 | 0.82 | 0.26 | asserted 0.93 |
| s7 | It gives a base for identity criterion of an evolving object, simplifies the definition of basic Darwinian mechanism and changes "life on the edge of chaos" to "life evolves in the half-chaos of not fully random systems". | interpretation 1.00 | 0.76 | 0.76 | asserted 0.99 |
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Original abstract
The research concerns the dynamics of complex autonomous Kauffman networks. The article defines and shows using simulation experiments half-chaotic networks, which exhibit features much more similar to typically modeled systems like a living, technological or social than fully random Kauffman networks. This makes a large change of widely taken view in the dynamics of complex networks. Current theory predicts that random autonomous systems can be either ordered or chaotic with fast phase transition between them. However, modeled adapted systems are not fully random, they are usually stable, but the estimated parameters are usually "chaotic", they place the fully random networks in the chaotic regime, far from the narrow phase transition. It is showed that among the not fully random systems with "chaotic parameters", a large third state called half-chaos exists, which simultaneously exhibit small (ordered) and large (chaotic) reactions for small disturbances in similar share. The discovery of half-chaos frees modeling of adapted systems from sharp restrictions; it allows to use "chaotic parameters" and get a nearly stable system more similar to modeled one. It gives a base for identity criterion of an evolving object, simplifies the definition of basic Darwinian mechanism and changes "life on the edge of chaos" to "life evolves in the half-chaos of not fully random systems".
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