Nonlinear Thermodynamics and Social Science Modeling: <i>Fad Cycles, Cultural Development and Identificational Slips</i>

Khalil, Elias L.

doi:10.1111/j.1536-7150.1995.tb03247.x

Cited by 19 publications

(3 citation statements)

References 25 publications

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“…Helbing (2010: 325) lo denomina enfoque fisicalista y consiste en la transferencia de propiedades de muchos sistemas de partículas a los sistemas sociales. La visión no ha estado exenta de críticas (Khalil 1995;Helmreich 1998Helmreich , 1999.…”

Section: Introductionunclassified

Sistemas complejos adaptativos y simulación computacional en Arqueología

Gordó

2017

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ReSumenTradicionalmente el concepto "complejidad" se utiliza como sinónimo de "sociedad compleja" para referirse a grupos humanos que presentan determinadas característi-cas tales como urbanismo, desigualdad y jerarquización. Con la introducción de los Sistemas no lineales y de los Sistemas Complejos a la disciplina arqueológica dicho concepto está siendo matizado. Este viraje teórico ha supuesto el auge de las simulaciones computacionales como método de análisis de procesos históricos. Este trabajo tiene un doble objetivo: presentar la corriente teórica caracterizada por el pensamiento generativo que se está llevando a cabo en la disciplina arqueológica e ilustrar una aplicación concreta de la simulación computacional basada en agentes a un problema arqueológico: la dispersión de las primeras producciones cerámicas en el Mediterráneo occidental.

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Section: Introductionunclassified

Sistemas complejos adaptativos y simulación computacional en Arqueología

Gordó

2017

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“…Boolean networks are a particularly simple form of complex system and have been found to be useful models in the study of a wide range of systems, including gene regulatory systems [15][16][17][18][19], spin glasses [9,10], evolution [21], social sciences [13,14,20,23], the stock market [7], circuit theory and computer science [12,22].…”

Section: Introductionmentioning

confidence: 99%

Simplifying Boolean Networks

Richardson

2005

Advs. Complex Syst.

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This paper explores the compressibility of complex systems by considering the simplification of Boolean networks. A method, which is similar to that reported by Bastolla and Parisi,4,5 is considered that is based on the removal of frozen nodes, or stable variables, and network "leaves," i.e. those nodes with outdegree = 0. The method uses a random sampling approach to identify the minimum set of frozen nodes. This set contains the nodes that are frozen in all attractor schemes. Although the method can over-estimate the size of the minimum set of frozen nodes, it is found that the chances of finding this minimum set are considerably greater than finding the full attractor set using the same sampling rate. Given that the number of attractors not found for a particular Boolean network increases with the network size, for any given sampling rate, such a method provides an opportunity to either fully enumerate the attractor set for a particular network, or improve the accuracy of the random sampling approach. Indeed, the paper also shows that when it comes to the counting of attractors in an ensemble of Boolean networks, enhancing the random sample method with the simplification method presented results in a significant improvement in accuracy.

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“…Kauffman nets [1] have been used to model the complex behavior of dynamical systems ranging from gene regulatory systems [2][3][4], spin glasses [5,6], evolution [7], social sciences [8][9][10][11], to the stock market [12]. A Kauffman net consists of N boolean variables or spins, each of which is either "+1" or "-1" at each time t = 0, 1, 2, .…”

Section: Introductionmentioning

confidence: 99%

Reversible Boolean networks

Coppersmith¹,

Kadanoff²,

Zhang³

2001

Physica D: Nonlinear Phenomena

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We continue our consideration of a class of models describing the reversible dynamics of N Boolean variables, each with K inputs. We investigate in detail the behavior of the Hamming distance as well as of the distribution of orbit lengths as N and K are varied. We present numerical evidence for a phase transition in the behavior of the Hamming distance at a critical value K c ≈ 1.65 and also an analytic theory that yields the exact bounds on 1.5 ≤ K c ≤ 2.We also discuss the large oscillations that we observe in the Hamming distance for K < K c as a function of time as well as in the distribution of cycle lengths as a function of cycle length for moderate K both greater than and less than K c . We propose that local structures, or subsets of spins whose dynamics are not fully coupled to the other spins in the system, play a crucial role in generating these oscillations. The simplest of these structures are linear chains, called linkages, and rings, called circuits. We discuss the properties of the linkages in some detail, and sketch the properties of circuits. We argue that the observed oscillation phenomena can be largely understood in terms of these local structures.

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Nonlinear Thermodynamics and Social Science Modeling: Fad Cycles, Cultural Development and Identificational Slips

Cited by 19 publications

References 25 publications

Sistemas complejos adaptativos y simulación computacional en Arqueología

Sistemas complejos adaptativos y simulación computacional en Arqueología

Simplifying Boolean Networks

Reversible Boolean networks

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