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59
Complex networks: Structure and dynamics
, 2006
"... Coupled biological and chemical systems, neural networks, social interacting species, the Internet and the World Wide Web, are only a few examples of systems composed by a large number of highly interconnected dynamical units. The first approach to capture the global properties of such systems is to ..."
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Cited by 183 (5 self)
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Coupled biological and chemical systems, neural networks, social interacting species, the Internet and the World Wide Web, are only a few examples of systems composed by a large number of highly interconnected dynamical units. The first approach to capture the global properties of such systems is to model them as graphs whose nodes represent the dynamical units, and whose links stand for the interactions between them. On the one hand, scientists have to cope with structural issues, such as characterizing the topology of a complex wiring architecture, revealing the unifying principles that are at the basis of real networks, and developing models to mimic the growth of a network and reproduce its structural properties. On the other hand, many relevant questions arise when studying complex networks ’ dynamics, such as learning how a large ensemble of dynamical systems that interact through a complex wiring topology can behave collectively. We review the major concepts and results recently achieved in the study of the structure and dynamics of complex networks, and summarize the relevant applications of these ideas in many different disciplines,
Computability and Evolutionary Complexity: Markets as Complex Adaptive Systems
 CAS). Economic Journal 115 (504) (2005), F159–F192. Available online at SSRN: http://ssrn.com/abstract=745578
"... Few will argue that the epiphenomena of biological systems and socioeconomic systems are anything but complex. The purpose of this Feature is to examine critically and contribute to the burgeoning multidisciplinary literature on markets as complex adaptive systems (CAS). The new sciences of compl ..."
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Cited by 26 (9 self)
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Few will argue that the epiphenomena of biological systems and socioeconomic systems are anything but complex. The purpose of this Feature is to examine critically and contribute to the burgeoning multidisciplinary literature on markets as complex adaptive systems (CAS). The new sciences of complexity, the principles of selforganisation and emergence along with the methods of evolutionary computation and artificially intelligent agent models have been developed in a multidisciplinary fashion. The cognoscenti here consider that complex systems whether natural or artificial, physical, biological or socioeconomic can be characterised by a unifying set of principles. Further, it is held that these principles mark a paradigm shift from earlier ways of viewing such phenomenon. The articles in this Feature aim to provide detailed insights and examples of both the challenges and the prospects for economics that are offered by the new methods of the complexity sciences. The applicability or not of the optimisation framework of conventional economics depends on the domain of the problem and in particular the modern theories behind noncomputability are outlined to explain why adaptive or emergent methods of computation and agentbased
Complex systems analysis of series of blackouts: cascading failure, critical points, and selforganization
 Chaos
, 2004
"... We give a comprehensive account of a complex systems approach to large blackouts caused by cascading failure. Instead of looking at the details of particular blackouts, we study the statistics, dynamics and risk of series of blackouts with approximate global models. North American blackout data sugg ..."
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Cited by 25 (5 self)
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We give a comprehensive account of a complex systems approach to large blackouts caused by cascading failure. Instead of looking at the details of particular blackouts, we study the statistics, dynamics and risk of series of blackouts with approximate global models. North American blackout data suggests that the frequency of large blackouts is governed by a power law. This result is consistent with the power system being a complex system designed and operated near criticality. The power law makes the risk of large blackouts consequential and implies the need for nonstandard risk analysis. Power system overall load relative to operating limits is a key factor affecting the risk of cascading failure. Blackout models and an abstract model of cascading failure show that there are critical transitions as load is increased. Power law behavior can be observed at these transitions. The critical loads at which blackout risk sharply increases are identifiable thresholds for cascading failure and we discuss approaches to computing the proximity to cascading failure using these thresholds. Approximating cascading failure as a branching process suggests ways to compute and monitor criticality by quantifying how much failures propagate. Inspired by concepts from selforganized criticality, we suggest that power system operating margins evolve slowly to near criticality and confirm this idea using a blackout model. Mitigation of blackout risk should take care to account for counterintuitive effects in complex selforganized critical systems. For example, suppressing small blackouts could lead the system to be operated closer to the edge and ultimately increase the risk of large blackouts. 1
Evidence for selforganized criticality in a time series of electric power system blackouts
 IEEE TRANSACTIONS ON POWER SYSTEMS
, 2004
"... We analyze a 15year time series of North American electric power transmission system blackouts for evidence of selforganized criticality.The probability distribution functions of various measures of blackout size have a power tail and R/S analysis of the time series shows moderate long time corr ..."
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Cited by 21 (5 self)
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We analyze a 15year time series of North American electric power transmission system blackouts for evidence of selforganized criticality.The probability distribution functions of various measures of blackout size have a power tail and R/S analysis of the time series shows moderate long time correlations.Moreover, the same analysis applied to a time series from a sandpile model known to be selforganized critical gives results of the same form.Thus the blackout data is consistent with selforganized criticality. A qualitative explanation of the complex dynamics observed in electric power system blackouts is suggested.
Blackout mitigation assessment in power transmission systems
 36th Hawaii International Conference on System Sciences
, 2003
"... Electric power transmission systems are a key infrastructure and blackouts of these systems have major direct and indirect consequences on the economy and national security. Analysis of North American Electrical Reliability Council blackout data suggests the existence of blackout size distributions ..."
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Cited by 18 (9 self)
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Electric power transmission systems are a key infrastructure and blackouts of these systems have major direct and indirect consequences on the economy and national security. Analysis of North American Electrical Reliability Council blackout data suggests the existence of blackout size distributions with power tails. This is an indication that blackout dynamics behave as a complex dynamical system. Here, we investigate how these complex system dynamics impact the assessment and mitigation of blackout risk. The mitigation of failures in complex systems needs to be approached with care. The mitigation efforts can move the system to a new dynamic equilibrium while remaining near criticality and preserving the power tails. Thus, while the absolute frequency of disruptions of all sizes may be reduced, the underlying forces can still cause the relative frequency of large disruptions to small disruptions to remain the same. Moreover, in some cases, efforts to mitigate small disruptions can even increase the frequency of large disruptions. This occurs because the large and small disruptions are not independent but are strongly coupled by the dynamics. 1.
GILK: A dynamic instrumentation tool for the Linux Kernel
 In Computer Performance Evaluation / TOOLS
, 2002
"... This paper describes a dynamic instrumentation tool for the Linux Kernel which allows a stock Linux kernel to be modi ed while in execution, with instruments implemented as kernel modules. The Intel x86 architecture poses a particular problem, due to variable length instructions, which this paper ad ..."
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Cited by 17 (2 self)
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This paper describes a dynamic instrumentation tool for the Linux Kernel which allows a stock Linux kernel to be modi ed while in execution, with instruments implemented as kernel modules. The Intel x86 architecture poses a particular problem, due to variable length instructions, which this paper addresses for the rst time. Finally we present a short case study illustrating its use in understanding i/o behaviour in the kernel. The source code is freely available for download.
Human Cognition and a Pile of Sand: A Discussion on Serial Correlations and Selforganized Criticality
, 2005
"... ... framework of cognitive psychology in favor of the framework of nonlinear dynamical systems theory. Van Orden et al. presented evidence that“purposive behavior originates in selforganized criticality ” (p. 333). Here, the authors show that Van Orden et al.’s analyses do not test their hypotheses ..."
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Cited by 9 (2 self)
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... framework of cognitive psychology in favor of the framework of nonlinear dynamical systems theory. Van Orden et al. presented evidence that“purposive behavior originates in selforganized criticality ” (p. 333). Here, the authors show that Van Orden et al.’s analyses do not test their hypotheses. Further, the authors argue that a confirmation of Van Orden et al.’s hypotheses would not have constituted firm evidence in support of their framework. Finally, the absence of a specific model for how selforganized criticality produces the observed behavior makes it very difficult to derive testable predictions. The authors conclude that the proposed paradigm shift is presently unwarranted.
Stochastic porous media equation and selforganized criticality
 Comm. Math. Phys
"... Abstract. The existence and uniqueness of nonnegative strong solutions for stochastic porous media equations with noncoercive monotone diffusivity function and Wiener forcing term is proven. The finite time extinction of solutions with high probability is also proven in 1D. The results are relevant ..."
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Cited by 8 (6 self)
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Abstract. The existence and uniqueness of nonnegative strong solutions for stochastic porous media equations with noncoercive monotone diffusivity function and Wiener forcing term is proven. The finite time extinction of solutions with high probability is also proven in 1D. The results are relevant for selforganized critical behaviour of stochastic nonlinear diffusion equations with critical states.
Propagating spin modes in canonical quantum gravity”, grqc/9810024. 36 Penrose R
, 1998
"... One of the main results in canonical quantum gravity is the introduction of spin network states as a basis on the space of kinematical states. To arrive at the physical state space of the theory though we need to understand the dynamics of the quantum gravitational states. To this aim we study a mod ..."
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Cited by 6 (0 self)
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One of the main results in canonical quantum gravity is the introduction of spin network states as a basis on the space of kinematical states. To arrive at the physical state space of the theory though we need to understand the dynamics of the quantum gravitational states. To this aim we study a model in which we allow for the spins, labeling the edges of spin networks, to change according to simple rules. The gauge invariance of the theory, restricting the possible values for the spins, induces propagating modes of spin changes. We investigate these modes under various assumptions about the parameters of the model.
Minimal agent based model for financial markets II: statistical properties of the linear and multiplicative dynamics. to be submitted
, 2008
"... We introduce a minimal Agent Based Model for financial markets to understand the nature and SelfOrganization of the Stylized Facts. The model is minimal in the sense that we try to identify the essential ingredients to reproduce the main most important deviations of price time series from a Random ..."
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Cited by 5 (2 self)
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We introduce a minimal Agent Based Model for financial markets to understand the nature and SelfOrganization of the Stylized Facts. The model is minimal in the sense that we try to identify the essential ingredients to reproduce the main most important deviations of price time series from a Random Walk behavior. We focus on four essential ingredients: fundamentalist agents which tend to stabilize the market; chartist agents which induce destabilization; analysis of price behavior for the two strategies; herding behavior which governs the possibility of changing strategy. Bubbles and crashes correspond to situations dominated by chartists, while fundamentalists provide a long time stability (on average). The Stylized Facts are shown to correspond to an intermittent behavior which occurs only for a finite value of the number of agents N. Therefore they correspond to finite size effect which, however, can occur at different time scales. We propose a new mechanism for the SelfOrganization of this state which is linked to the existence of a threshold for the agents to be active or not active. The feedback between price fluctuations and number of active agents represent a crucial element for this state of SelfOrganizedIntermittency. The model can be easily generalized to consider more realistic variants. 1