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Foundations of Complex-Systems Theories
Abstract
Complex behaviour can occur in any system made up of large numbers of interacting constituents, be they atoms in a solid, cells in a living organism, or consumers in a national economy. Analysis of this behaviour often involves making important assumptions and approximations, the exact nature of which vary from subject to subject. Foundations of Complex-system Theories begins with a description of the general features of complexity and then examines a range of important concepts, such as theories of composite systems, collective phenomena, and stochastic processes. Each topic is discussed with reference to the fields of statistical physics, evolutionary biology, and economics, thereby highlighting recurrent themes in the study of complex systems. This detailed yet nontechnical book will appeal to anyone who wants to know more about complex systems and their behaviour. It will also be of great interest to specialists studying complexity in the physical, biological, and social sciences.
... To date, most work in CAS has been conducted in highly abstracted and artificial systems like cellular automata and genetic computer algorithms, and in the fields of economics, sociology, microbiology , and medicine. Although CAS is in its infancy and remains in search of fundamental principles (Auyang, 1998), basic concepts from CAS can be extracted from its literature. The specific objectives of this paper are to (a) demonstrate that an important reason why the individual-based approach to ecological modelling has not proven to be as productive as anticipated is the lack of a theoretical framework, and (b) present some key concepts of CAS that may be valuable as a way of thinking about, designing, and evaluating IBMs. ...
... Understanding and analyzing systems as the complex emergent properties of adaptive individuals is a new and potentially revolutionary way of approaching a number of sciences. The essence of CAS is the study of systems built of individual agents that are capable of adapting as they interact with each other and with an environment, and especially the attempt to understand how the characteristics of individuals affect the systemlevel responses (Auyang, 1998). The focus of CAS research has been from the bottom up, describing kinds of agents and environments and then experimentally finding out what kind of complex dynamics are exhibited by the system of agents. ...
... Examples range from interesting patterns emerging from the simplest cellular automata to the human brain's function emerging from the limited capabilities of individual neurons . Understanding how system-level properties emerge from the characteristics of individual agents is the fundamental problem of CAS research (Auyang, 1998) and has been described by Levin (1999) as the most important challenge for ecologists. Models in which complex and realistic system responses emerge naturally from simple individual behaviors should be very appealing to ecologists, because such models are more likely to represent the basic mechanisms driving ecosystems. ...
Individual-based models (IBMs) have long been proposed as a key tool for understanding and predicting ecosystem complexities, yet the contribution of this approach to basic or applied ecology has been less than anticipated. Fundamental reasons for the disappointing contribution of IBMs have been, in the current absence of a theoretical foundation for IBMs, conceptual flaws in model formulation and the failure to address critical computer implementation issues. Researchers in the new field of Complex Adaptive Systems (CAS) study how complex behaviors emerge in systems of relatively simple interacting individuals. Research on CAS, while still new and informal, has identified key concepts for making individual-based systems realistic. I propose that explicit consideration of the following concepts from CAS should make the design of IBMs less ad hoc and more likely to produce models of value for basic and applied ecology: (1) Emergence: what behaviors and population dynamics should emerge from the model's mechanistic representation of key processes vs. being imposed on the model as empirical relations? How should individual traits be modeled so that realistic population responses emerge?; (2) Adaptation: given the model's temporal and spatial scales, what adaptive processes of individuals should be modeled? What mechanisms do individuals use to adapt in response to what environmental forces?; (3) Fitness and strategy: what measures of fitness are appropriate to use as the basis for modelling decision making? Should fitness measures change with life history state?; (4) State-based responses: how should decision processes depend on an individual's state?; (5) Prediction: anticipating decision outcomes appears essential for modelling many behaviors; what are realistic assumptions about how organisms predict the consequences of decisions?; (6) Computer implementation: what user interfaces are necessary to make the model, and especially individual behaviors, observable and testable? How will the model's full design and computer implementation be documented and tested so results are reproducible and valid?
... The proposed CAS theory has provided new ideas for people to recognize, control, and manage complex systems, and is widely used in economic systems, ecosystems, and social systems (Auyang, 1999a(Auyang, , 1999bGuo, 2017;Krieger, 2001). The study of complexity is also valued by Chinese scholars, whose research on the science of complexity mainly covers the three aspects of methodology, mathematical theory, and application, and involves many subjects including geography, economics, biology, physics, management and philosophy (Comfort, 1999;Song, 2005). ...
... • Cheng and Chen (2006) analyzed the self-organization characteristics of the city's overall system and urban subsystems, and pointed out that urban spatial aggregation and diffusion exhibit selforganization, and that the process of urban evolution has an obvious self-organization mechanism. Quantitative research Related quantitative research primarily introduces complex systems to the simulation of urban spatial systems, including urban spatial structures, transportation networks, urban boundaries, etc., to reveal the selforganizing mechanism of urban system evolution ( Allen, 1997;Chang et al., 2018;Krieger, 2001;Kittock, 1993). Common quantitative models include dynamic models, cellular automata (CA) models, and fractal theory models. ...
With the continuous development of urbanization, and increasing uncertainties and risks, resilience has become an important criterion for urban safety. As a dynamic and open spatial system, the urban system presents typical complex features. Thus, the understanding of urban resilience from the perspective of complex systems theory is helpful to achieve a full understanding of the composition and functioning mechanism of urban systems, and to then improve the scientific nature of urban system cognition and research. In this article, the literature on urban resilience is first reviewed, and it is found that the related research on resilience assessment has yielded some assessment methods. Then, based on complex adaptive systems (CAS) theory and combined with its seven basic characteristics, the basic characteristics of complex urban systems are summarized from the perspective of the principle of the urban system action mechanism. On this basis, a framework of complex urban systems is constructed from three aspects, namely the system environment, system elements and system structure, and the assessment methods of the urban system resilience for each aspect are explored. This study not only expands the research on urban system resilience assessment, but also provides a reference for urban safety development and resilience improvement.
... This process of building a complex model from simpler uncoupled (or weakly coupled) parts was first suggested by Simon (1962) and is often called " hierarchical decomposition. " In complexity theory by Auyang (1998), this process of building a complex system from its fundamental parts is often called " reductionism, " where the behavior of the system is realized from the sum of its independent parts. Predictions of applications (scenarios) against IETs for an M&S capability are generated by forward propagating the posterior  i distribution through the relevant models. ...
... There is a 'thin' construal of the metaphor, where the particular ways in which the sciences construct their proprietary representations of nature is left unspecified. For this version of the scheme, an alternative, though related, presentation of the idea is Auyang's geometrical model: she proposes to think of the various sciences as providing local coordinate maps (in the sense of differential geometry) for a manifold, in this instance the objective world (Auyang, 1998: 74–75). By contrast, a cognitive approach to science leads to a 'thick' interpretation, which draws on the similarities between vision and science as natural processes. ...
... ABMs often model complex dynamic systems and focus on the macroscale, or " emergent " phenomena that result from the decentralized decisions of and interactions between agents. Emergence can be understood within the geographical context of level or scale, as emergent phenomena at one level may form the units of interaction, or drivers of change, at a higher level (Auyang, 1998). In contrast to many traditional dynamic simulation models, a set of global equilibrium conditions is not imposed in ABMs. ...
This paper presents an agent-based model of land use designed to explore the impacts of edge-effect externalities—distance-dependent spatial externalities—on land-use pattern. While the impacts of externalities on aspatial economics measures such as equilibrium land rents and the distribution of economic activity are well explored, links between externalities and landscape pattern are not well understood. This gap reflects a more general gap between aspatial theoretical land-use models and descriptive, pattern-based empirical analysis. The model presented in this paper, designed to link changes in socioeconomic parameters to changes in macroscale measures of landscape pattern, was developed with the specific goal of formally bridging this gap. The model simulates land-use decisions of parcel managers in an environment where potential conflicts between urban and agricultural land uses affect the payoffs to particular land uses. In the model, spatial and aspatial macroscale outcomes emerge from the independent, but dynamically linked, decisions of individual parcel managers. Land-use composition, land-use pattern, and the location of land uses are jointly determined, and interactions between composition and pattern feedback to microlevel landowner decisions through endogenous land rents. The paper demonstrates a series of results. First, the paper demonstrates the economic inefficiency of landscape fragmentation when edge-effect externalities are present and illustrates a series of landscape metrics appropriate to measure this fragmentation. Second, the agent-based model is used to demonstrate links between externality impacts and landscape pattern: that conflicts between urban and residential land users lead to a more compact urban form, that when the profitability of agricultural production is reduced by proximity to urban land, the urban–rural fringe expands to a socially inefficient degree, and that conflicts between urban land users can lead to fragmented patterns of urban development consistent with existing definitions of urban sprawl. Finally, the paper concludes by proposing a methodology for establishing the robustness of the model’s conclusions over a wide range of parameter values.
We observe a Quantum Brownian Motion (QBM) Model Universe in conjunction with
recently established Entanglement Relativity and Parallel Occurrence of
Decoherence. The Parallel Occurrence of Decoherence establishes the
simultaneous occurrence of decoherence for two mutually irreducible structures
(decomposition into subsystems) of the total QBM model universe. First we find
that Everett world branching for one structure excludes branching for the
alternate structure and in order to reconcile this situation branching cannot
be allowed for either of the structures considered. Second, we observe the
non-existence of a third, "emergent structure", that could approximate both
structures and also be allowed to branch. Ultimately we find unless
world-branching requires additional criteria or conditions, or there is a
privileged structure, that we provide a valid model that cannot be properly
described by the Everett Interpretation of Quantum Mechanics.
We observed a new pattern of nonlinear behavior of seismicity. We studied the scaling property of the interevent time series of the seismic sequence for Puer area in China by using the methods of the local scaling property, the generalized dimension spectrum, and the correlation dimension. It is indicated that there are clear characteristic variations of local scaling property and generalized dimension spectrum prior to Puer M6.4 earthquake while there is no characteristic variation of the correlation dimension. This result suggests that the choice of suitable methods is needed for the purpose of getting valuable information about the scale invariance in application of the three methodologies. The major difference between the characteristic variation of local scaling property and the other patterns of nonlinear behavior of seismicity such as the variations of the generalized dimension spectrum and fractal dimension of seismicity before large earthquakes is in the description of scaling property: the generalized dimension spectrum and fractal dimension focus on the global description of the scaling properties, while the local scaling property emphasis the local features. Therefore, the characteristic variation of local scaling property before Puer M6.4 earthquake presents a new pattern of nonlinear behavior of seismicity.
This paper is meant as an introductive work on the research field of Organic Computing (OC). It gives information on the main goals of Organic Computing and provide the basic ideas behind it. Furthermore, it explains the basic termi- nology that is required in the research field of OC and give some examples for recent work. The conclusion gives a brief overview on how the position in OC is today. Due to the fact that this is an introductive paper, it will contain numerous references for supplemental reading.
The systemic theory associates open systems and complexity closely. This article presents a particular articulation between these two concepts using the Systemion Model. Two types of opening are defined, characterized and illustrated using examples.
Nowadays we are often faced with huge databases resulting from the rapid
growth of data storage technologies. This is particularly true when dealing
with music databases. In this context, it is essential to have techniques and
tools able to discriminate properties from these massive sets. In this work, we
report on a statistical analysis of more than ten thousand songs aiming to
obtain a complexity hierarchy. Our approach is based on the estimation of the
permutation entropy combined with an intensive complexity measure, building up
the complexity-entropy causality plane. The results obtained indicate that this
representation space is very promising to discriminate songs as well as to
allow a relative quantitative comparison among songs. Additionally, we believe
that the here-reported method may be applied in practical situations since it
is simple, robust and has a fast numerical implementation.
Purpose
The purpose of this paper is to discuss the origin of variance and beta as risk measures and to identify their shortcomings as perceived risk metrics.
Design/methodology/approach
The paper analyses seminal literature from economics, psychology, and neuroscience that have relevance to financial risk.
Findings
There is empirical evidence that investors are loss‐averse and affectively influenced. Variance and beta as conventionally calculated are flawed because they do not take into account the inherent indeterminacy of the investor's world.
Practical implications
The paper demonstrates that perceived risk will be systematically mis‐measured and that risk premium/return anomalies will prevail until a more affective and multidimensional risk metric is utilized.
Originality/value
The value of the paper lies in its concise and clear identification of financial risk measurement issues and a suggested direction for remediation.
The neo-Darwinian view of evolution centres upon the role of the gene. Here there seems to be little scope for self-organization. This conclusion is reinforced by traditional models of polymorphism in terms of allele frequencies in a mean-field gene-pool. However, models based on phenotypes, and including nonlinear and collective effects, suggest that evolution can indeed be viewed as a process whereby the ecosystem self-organizes. Here we focus on the phenomenon of speciation, and discuss a series of phenotypic models which together illuminate some of the issues surrounding the role of self-organization, including new approaches to fitness landscapes and species selection. All of these models represent speciation as a symmetry-breaking bifurcation, but in different mathematical contexts including deterministic dynamical systems, stochastic dynamical systems, and iterated function schemes. The main conclusions are surprisingly robust, despite the diversity of the models.
Local interactions, biotic and abiotic, can have a strong influence on the large-scale properties of ecosystems. However, ecological models often explore the influence of local biotic interactions where physical disturbance is included as a large-scale and imposed source of variability but is not allowed to interact with biotic processes at the local scale. In marine intertidal communities dominated by mussels, wave disturbances create gaps in the mussel bed that recover through a successional sequence. We present a lattice model of mussel disturbance dynamics that allows local interactions between wave disturbance and mussel recolonization, in which each cell of the lattice can be empty, occupied by a mussel bed element, or disturbed (which corresponds to a newly disturbed cell that has unstable edges). As in natural ecosystems, wave disturbance can also spread from disturbed to adjacent occupied cells, and recolonization can also spread from occupied to adjacent empty cells. We first validate the local rules from artificial gap experiments and from natural gap monitoring along the Oregon coast. We analyze the properties of the model system as a function of different oceanographic forcings of productivity and disturbance. We show that the mussel bed can go through phase transitions characterized by a large sensitivity of mussel cover and patterns to oceanographic forcings but also that criticality (scale invariance) is observed over wide ranges of parameters, which suggests self-organization. We also show that spatial patterns in the intertidal can provide a robust signature of local processes and can inform about oceanographic regimes. We do so by comparing the large-scale patterns of the simulation (scaling exponents) with field data, which suggest that some experimental sites are close to criticality. Our results suggest that regional patterns in disturbed populations can be explained by local biotic and abiotic processes submitted to oceanographic forcing.
The engineering and design of self-organizing systems with emergent properties is a long-standing problem in the field of complex and distributed systems, for example in the engineering of self-organizing Multi-Agent Systems. The problem of combining engineering with emergence - to find a simple rule for a complex pattern - equals the problem of science in general. Therefore the answers are similar, and the scientific method is the general solution to the problem of engineering complex systems.
Self-Organization is of growing importance for large distributed computing systems. In these systems, a central control and manual management is exceedingly difficult or even impossible. Emergence is widely recognized as the core principle behind self-organization. Therefore the idea to use both principles to control and organize large-scale distributed systems is very attractive and not so far off. Yet there are many open questions about emergence and self-organization, ranging from a clear definition and scientific understanding to the possible applications in engineering and technology, including the limitations of both concepts. Self-organizing systems with emergent properties are highly desirable, but also very challenging. We pose ten central questions about emergence, give preliminary answers, and identify four basic limits of self-organization: a size limit, a place limit, a complexity limit and finally a combinatorial limit.
A set of general physical principles is proposed as the structural basis for the theory of complex systems. First the concept of harmony is analyzed and its different aspects are uncovered. Then the concept of reflection is defined and illustrated by suggestive examples. Later we propose the principle of (random) projection of symmetrically expanded prereality as the main description method of complex systems.
The immediate purpose of the paper was neither to review the basic definitions of percolation theory nor to rehearse the general physical notions of universality and renormalization (an important technique to be described in Part Two). It was rather to describe as concretely as possible, although in hypothetical form, the geometric aspects of universality, especially conformal invariance, in the context of percolation, and to present the numerical results that support the hypotheses. On the other hand, one ulterior purpose is to draw the attention of mathematicians to the mathematical problems posed by the physical notions. Some precise basic definitions are necessary simply to orient the reader. Moreover a brief description of scaling and universality on the one hand and of renormalization on the other is also essential in order to establish their physical importance and to clarify their mathematical content. Comment: 61 pages. Abstract added in migration
The partition function with boundary conditions for various two-dimensional Ising models is examined and previously unobserved properties of conformal invariance and universality are established numerically. Comment: 96 pages, 57 figures. Revised version. New paragraph added to answer questions raised by referee. To appear in J.Stat.Phys. vol 98, issue 1/2 (2000)
Preface 1. The Division of Labor: The Factory 2. Taking Apart and Putting Together: The Clockworks, the Calculus, and the Computer 3. Freedom and Necessity: Family and Kinship 4. The Vacuum and the Creation: Setting a Stage 5. Handles, Probes, and Tools: A Rhetoric of Nature Suggestions for Further Reading Notes Index of Topics Index of Names and Subjects
In this insightful work, Martin H. Krieger shows what physicists are really doing when they employ mathematical models as research tools. He argues that the technical details of these complex calculations serve not only as a means to an end, but also reveal key aspects of the physical properties they model. Krieger's lucid discussions will help readers to appreciate the larger physical issues behind the mathematical detail of modern physics and gain deeper insights into how theoretical physicists work. Constitutions of Matter is a rare, behind-the-scenes glimpse into the world of modern physics. "[Krieger] provides students of physics and applied mathematics with a view of the physical forest behind the mathematical trees, historians and philosophers of science with insights into how theoretical physicists go about their work, and technically advanced general readers with a glimpse into the discipline."âScitech Book News