Complex systems is the subject of a diverse variety of sciences Science is a systematic enterprise of gathering knowledge about nature and organizing and condensing that knowledge into testable laws and theories. As knowledge has increased, some methods have proved more reliable than others, and today the scientific method is the standard for science. It includes the use of careful observation, experimentation, and professional practice methods. It is often overshadowed by the representation of natural physical organization with systems of equations, the main subject below. In the study of complex systems that are less usefully represented with equations various other kinds of narratives and methods for identifying, boundaries, exploring, designing and interacting with complex systems are used. A more broad view of the various disciplines and practice methodologies using the complex systems approach is found on the Encyclopedia of the Earth.[1]

The equations from which complex system models are developed generally derive from statistical physics, information theory and non-linear dynamics, and represent organized but unpredictable behaviors of systems System is a set of interacting or interdependent entities forming an integrated whole of nature that are considered fundamentally complex In general usage, complexity tends to be used to characterize something with many parts in intricate arrangement. The study of these complex linkages is the main goal of network theory and network science. In science there are at this time a number of approaches to characterizing complexity, many of which are reflected in this article. In a. The physical manifestations of such systems cannot be defined, so the usual choice is to refer to "the system" as the mathematical information model, without referring to the undefined physical subject the model represents. One of a variety of journals using this approach to complexity is Complex Systems

Such systems are used to model processes in computer science Computer science or computing science is the study of the theoretical foundations of information and computation, and of practical techniques for their implementation and application in computer systems. It is frequently described as the systematic study of algorithmic processes that create, describe, and transform information. Computer science, biology Biology is a natural science concerned with the study of life and living organisms, including their structure, function, growth, origin, evolution, distribution, and taxonomy, economics Complexity economics is the application of complexity science to the problems of economics. It is one of the four C's of a new paradigm surfacing in the field of economics. The four C's are complexity, chaos, catastrophe and cybernetics. This new mode of economic thought rejects traditional assumptions that imply that the economy is a closed, physics Physics is a natural science that involves the study of matter and its motion through space-time, as well as all applicable concepts, such as energy and force. More broadly, it is the general analysis of nature, conducted in order to understand how the universe behaves and many other fields. It is also called complex systems theory, complexity science, study of complex systems, sciences of complexity, non-equilibrium physics, and historical physics. A variety of abstract theoretical complex systems A complex system is a system composed of interconnected parts that as a whole exhibit one or more properties not obvious from the properties of the individual parts. This characteristic of every system is called emergence and is true of any system, not just complex ones[citation needed] is studied as a field of mathematics.

The key problems of complex systems are difficulties with their formal modeling Scientific modelling is the process of generating abstract, conceptual, graphical and/or mathematical models. Science offers a growing collection of methods, techniques and theory about all kinds of specialized scientific modelling. Also a way to read elements easily which have been broken down to the simplest form and simulation Simulation is used in many contexts, including the modeling of natural systems or human systems in order to gain insight into their functioning. Other contexts include simulation of technology for performance optimization, safety engineering, testing, training and education. Simulation can be used to show the eventual real effects of alternative. From such a perspective, in different research contexts complex systems are defined on the basis of their different attributes. Since all complex systems have many interconnected components, the science of networks Network science is a new and emerging scientific discipline that examines the interconnections among diverse physical or engineered networks, information networks, biological networks, cognitive and semantic networks, and social networks. This field of science seeks to discover common principles, algorithms and tools that govern network behavior and network theory Network theory is an area of computer science and network science and part of graph theory. It has application in many disciplines including particle physics, computer science, biology, economics, operations research, and sociology. Network theory concerns itself with the study of graphs as a representation of either symmetric relations or, more are important aspects of the study of complex systems. A consensus regarding a single universal definition of complex system A complex system is a system composed of interconnected parts that as a whole exhibit one or more properties not obvious from the properties of the individual parts. This characteristic of every system is called emergence and is true of any system, not just complex ones[citation needed] does not yet exist.

Contents

Overview

A Braitenberg Braitenberg vehicles are conceived in a thought experiment by the Italian-Austrian cyberneticist Valentino Braitenberg to illustrate in an evolutive way the abilities of simple agents. The vehicles represent the simplest form of behavior based artificial intelligence or embodied cognition, i.e. intelligent behavior that emerges from sensorimotor simulation, programmed in breve breve is a free, GPL software package that makes it easy to build 3D simulations of decentralized systems and artificial life. Users can define the behaviors of multi-agent systems in a 3D world and observe how they interact, an artificial life Artificial life is a field of study and an associated art form which examine systems related to life, its processes, and its evolution through simulations using computer models, robotics, and biochemistry. The discipline was named by Christopher Langton, an American computer scientist, in 1986. There are three main kinds of alife, named for their simulator

The study of mathematical complex system models is used for many scientific questions poorly suited to the traditional mechanistic conception provided by science.[2] Complex systems is therefore often used as a broad term encompassing a research approach to problems in many diverse disciplines including anthropology Anthropology is the study of humanity. Anthropology has origins in the natural sciences, the humanities, and social sciences. The term "anthropology", pronounced /ænθrɵˈpɒlədʒi/, is from the Greek ἄνθρωπος, anthrōpos, "human", and -λογία, -logia, "discourse" or "study", and was first, artificial intelligence Artificial intelligence is the intelligence of machines and the branch of computer science that aims to create it. Textbooks define the field as "the study and design of intelligent agents," where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who, artificial life Artificial life is a field of study and an associated art form which examine systems related to life, its processes, and its evolution through simulations using computer models, robotics, and biochemistry. The discipline was named by Christopher Langton, an American computer scientist, in 1986. There are three main kinds of alife, named for their, chemistry Chemistry is the science of matter and the changes it undergoes. The science of matter is also addressed by physics, but while physics takes a more general and fundamental approach, chemistry is more specialized, being concerned with the composition, behavior, structure, and properties of matter, as well as the changes it undergoes during chemical, computer science Computer science or computing science is the study of the theoretical foundations of information and computation, and of practical techniques for their implementation and application in computer systems. It is frequently described as the systematic study of algorithmic processes that create, describe, and transform information. Computer science, economics Economics is the social science that is concerned with the production, distribution, and consumption of goods and services. The term economics comes from the Ancient Greek οἰκονομία from οἶκος (oikos, "house") + νόμος (nomos, "custom" or "law"), hence "rules of the house(hold)". Current, evolutionary computation In computer science, evolutionary computation is a subfield of artificial intelligence that involves combinatorial optimization problems, earthquake An earthquake is the result of a sudden release of energy in the Earth's crust that creates seismic waves. Earthquakes are measured with a seismometer; a device which also records is known as a seismograph. The moment magnitude (or the related and mostly obsolete Richter magnitude) of an earthquake is conventionally reported, with magnitude 3 or prediction, meteorology Meteorology is the interdisciplinary scientific study of the atmosphere that focuses on weather processes and short term forecasting . Studies in the field stretch back millennia, though significant progress in meteorology did not occur until the eighteenth century. The nineteenth century saw breakthroughs occur after observing networks developed, molecular biology Molecular biology is the study of biology at a molecular level. The field overlaps with other areas of biology and chemistry, particularly genetics and biochemistry. Molecular biology chiefly concerns itself with understanding the interactions between the various systems of a cell, including the interactions between DNA, RNA and protein, neuroscience Neuroscience is the scientific study of the nervous system. Traditionally, neuroscience has been seen as a branch of biology. Nevertheless, it is currently an interdisciplinary science that involves other disciplines such as psychology, computer science, mathematics, physics, philosophy, and medicine. As a result, the scope of neuroscience has, physics Physics is a natural science that involves the study of matter and its motion through space-time, as well as all applicable concepts, such as energy and force. More broadly, it is the general analysis of nature, conducted in order to understand how the universe behaves, psychology Psychology is the scientific study of human or other animal mental functions and behaviors. In this field, a professional practitioner or researcher is called a psychologist. Psychologists are classified as social or behavioral scientists. Psychological research can be considered either basic or applied. Psychologists attempt to understand the and sociology Sociology is the study of society. It is a social science—a term with which it is sometimes synonymous—that uses various methods of empirical investigation and critical analysis to develop and refine a body of knowledge about human social activity, often with the goal of applying such knowledge to the pursuit of social welfare. Subject matter.

In these endeavors, scientists often seek simple non-linear coupling rules which lead to complex phenomena (rather than describe; see above), but this need not be the case. Human societies (and probably human brains The brain is the center of the nervous system in all vertebrate, and most invertebrate, animals. Some primitive animals such as jellyfish and starfish have a decentralized nervous system without a brain, while sponges lack any nervous system at all. In vertebrates, the brain is located in the head, protected by the skull and close to the primary) are complex systems in which neither the components nor the couplings are simple. Nevertheless, they exhibit many of the hallmarks of complex systems. It is worth remarking that non-linearity In mathematics, a nonlinear system is a system which is not linear, that is, a system which does not satisfy the superposition principle, or whose output is not proportional to its input. Less technically, a nonlinear system is any problem where the variable to be solved for cannot be written as a linear combination of independent components. A is not a necessary feature of complex systems modeling Systems modeling or systems modelling is the interdisciplinary study of the use of models to conceptualize and construct systems in business and IT development: macro-analyses that concern unstable equilibrium and evolution processes of certain biological/social/economic systems can usefully be carried out also by sets of linear equations, which do nevertheless entail reciprocal dependence between variable parameters.

Traditionally, engineering has striven to solve the non-linear system problem while bearing in mind that for small perturbations, most non-linear systems can be approximated with linear systems significantly simplifying the analysis. Linear systems represent the main class of systems for which general techniques for stability control and analysis exist. However, many physical systems (for example lasers Light Amplification by Stimulated Emission of Radiation is a mechanism for emitting electromagnetic radiation, typically light or visible light, via the process of stimulated emission. The emitted laser light is (usually) a spatially coherent, narrow low-divergence beam, that can be manipulated with lenses. In laser technology, "coherent) are inherently "complex systems" in terms of the definition above, and engineering practice must now include elements of complex systems research.

Information theory Information theory is a branch of applied mathematics and electrical engineering involving the quantification of information. Historically, information theory was developed by Claude E. Shannon to find fundamental limits on signal processing operations such as compressing data and on reliably storing and communicating data. Since its inception it applies well to the complex adaptive systems Complex adaptive systems are special cases of complex systems. They are complex in that they are diverse and made up of multiple interconnected elements and adaptive in that they have the capacity to change and learn from experience. The term complex adaptive systems (CAS) was coined at the interdisciplinary Santa Fe Institute (SFI), by John H, CAS, through the concepts of object oriented design, as well as through formalized concepts of organization and disorder that can be associated with any systems evolution process.

History

A history of Complexity Science

Complex Systems is a new approach to science that studies how relationships between parts give rise to the collective behaviors of a system System is a set of interacting or interdependent entities forming an integrated whole and how the system interacts and forms relationships with its environment.

The earliest precursor to modern complex systems theory can be found in the classical political economy of the Scottish Enlightenment The Scottish Enlightenment was the period in 18th century Scotland characterised by an outpouring of intellectual and scientific accomplishments. By 1750, Scots were among the most literate citizens of Europe, with an estimated 75% level of literacy, later developed by the Austrian school of economics The Austrian School is a heterodox school of economic thought that emphasizes the spontaneous organizing power of the price mechanism. Its name derives from the identity of its founders and early supporters, who were citizens of the old Austrian Habsburg Empire, including Carl Menger, Eugen von Böhm-Bawerk, Ludwig von Mises, and Friedrich Hayek, which says that order in market systems is spontaneous (or emergent) in that it is the result of human action, but not the execution of any human design.[3][4]

Upon this the Austrian school developed from the 19th to the early 20th century the economic calculation problem, along with the concept of dispersed knowledge In economics, dispersed knowledge is information that is dispersed throughout the marketplace, and is not in the hands of any single agent. All agents in the market have imperfect knowledge; however, they all have a good indicator of everyone else's knowledge and intentions, and that is the price, which were to fuel debates against the then-dominant Keynesian economics Keynesian economics is a macroeconomic theory based on the ideas of 20th century British economist John Maynard Keynes. Keynesian economics argues that private sector decisions sometimes lead to inefficient macroeconomic outcomes and therefore, advocates active policy responses by the public sector, including monetary policy actions by the central. This debate would notably lead economists, politicians and other parties to explore the question of computational complexity.

A pioneer in the field, and inspired by Karl Popper Sir Karl Raimund Popper, CH, FRS, FBA was an Austrian and British philosopher and a professor at the London School of Economics. He is widely regarded as one of the greatest philosophers of science of the 20th century; he also wrote extensively on social and political philosophy's and Warren Weaver Warren Weaver was an American scientist, mathematician, and science administrator. He is widely recognized as one of the pioneers of machine translation, and as an important figure in creating support for science in the United States's works, Nobel prize economist and philosopher Friedrich Hayek Friedrich August von Hayek CH , was an Austrian-born economist and philosopher known for his defence of classical liberalism and free-market capitalism against socialist and collectivist thought. He is considered by some to be one of the most important economists and political philosophers of the twentieth century. Hayek's account of how changing dedicated much of his work, from early to the late 20th century, to the study of complex phenomena,[5] not constraining his work to human economies but to other fields such as psychology Psychology is the scientific study of human or other animal mental functions and behaviors. In this field, a professional practitioner or researcher is called a psychologist. Psychologists are classified as social or behavioral scientists. Psychological research can be considered either basic or applied. Psychologists attempt to understand the,[6] biology Biology is a natural science concerned with the study of life and living organisms, including their structure, function, growth, origin, evolution, distribution, and taxonomy and cybernetics Cybernetics is the interdisciplinary study of the structure of regulatory systems. Cybernetics is closely related to control theory and systems theory. Both in its origins and in its evolution in the second-half of the 20th century, cybernetics is equally applicable to physical and social systems. Gregory Bateson Gregory Bateson was a British anthropologist, social scientist, linguist, visual anthropologist, semiotician and cyberneticist whose work intersected that of many other fields. Some of his most noted writings are to be found in his books, Steps to an Ecology of Mind (1972) and Mind and Nature (1979). Angels Fear (published posthumously in 1987) played a key role in establishing the connection between anthropology and systems theory; he recognized that the interactive parts of cultures function much like ecosystems.

Further Steven Strogatz from Sync stated that "every decade or so, a grandiose theory comes along, bearing similar aspirations and often brandishing an ominous-sounding C-name. In the 1960s it was cybernetics Cybernetics is the interdisciplinary study of the structure of regulatory systems. Cybernetics is closely related to control theory and systems theory. Both in its origins and in its evolution in the second-half of the 20th century, cybernetics is equally applicable to physical and social systems. In the 1970s it was catastrophe theory In mathematics, catastrophe theory is a branch of bifurcation theory in the study of dynamical systems; it is also a particular special case of more general singularity theory in geometry. Then came chaos theory in the '80s and complexity theory in the '90s." Later, complex science researches try to combine the natural science and the social science namely consilience science in the '00s and from the '10s, hyper-emotional research unifying science and art as in the Renáissance period is expected to emerge.[7]

Topics in the complex systems study

Challenges of managing complexity

As projects and acquisitions become increasingly complex, companies and governments are challenged to find effective ways to manage mega-acquisitions such as the Army Future Combat Systems. Acquisitions such as the FCS rely on a web of interrelated parts which interact unpredictably. As acquisitions become more network-centric and complex, businesses will be forced to find ways to manage complexity while governments will be challenged to provide effective governance to ensure flexibility and resiliency.[8]

Complexity and modeling

A way of modelling a Complex Adaptive System

One of Hayek's main contributions to early complexity theory is his distinction between the human capacity to predict the behaviour of simple systems and its capacity to predict the behaviour of complex systems through modeling. He believed that economics and the sciences of complex phenomena in general, which in his view included biology, psychology, and so on, could not be modeled after the sciences that deal with essentially simple phenomena like physics.[9] Hayek would notably explain that complex phenomena, through modeling, can only allow pattern predictions, compared with the precise predictions that can be made out of non-complex phenomena.[10]

Complexity and chaos theory

Complexity theory is rooted in Chaos theory, which in turn has its origins more than a century ago in the work of the French mathematician Henri Poincaré. Chaos is sometimes viewed as extremely complicated information, rather than as an absence of order.[11] The point is that chaos remains deterministic. With perfect knowledge of the initial conditions and of the context of an action, the course of this action can be predicted in chaos theory. As argued by Ilya Prigogine,[12] Complexity is non-deterministic, and gives no way whatsoever to precisely predict the future. The emergence of complexity theory shows a domain between deterministic order and randomness which is complex.[13] This is referred as the 'edge of chaos'.[14]

A plot of the Lorenz attractor

When one analyzes complex systems, sensitivity to initial conditions, for example, is not an issue as important as within the chaos theory in which it prevails. As stated by Colander,[15] the study of complexity is the opposite of the study of chaos. Complexity is about how a huge number of extremely complicated and dynamic set of relationships can generate some simple behavioral patterns, whereas chaotic behavior, in the sense of deterministic chaos, is the result of a relatively small number of non-linear interactions.[13]

Therefore, the main difference between Chaotic systems and complex systems is their history.[16] Chaotic systems do not rely on their history as complex ones do. Chaotic behaviour pushes a system in equilibrium into chaotic order, which means, in other words, out of what we traditionally define as 'order'. On the other hand, complex systems evolve far from equilibrium at the edge of chaos. They evolve at a critical state built up by a history of irreversible and unexpected events. In a sense chaotic systems can be regarded as a subset of complex systems distinguished precisely by this absence of historical dependence. Many real complex systems are, in practice and over long but finite time periods, robust. However, they do possess the potential for radical qualitative change of kind whilst retaining systemic integrity. Metamorphosis serves as perhaps more than a metaphor for such transformations.

Research centers, conferences, and journals

Institutes and research centers

Journals

Other resources

See also

Systems science portal

References

  1. ^ [http://www.eoearth.org/article/Complex_systems P.F. Henshaw 2009 Complex Systems, Encyclopedia of the Earth
  2. ^ http://www.narberthpa.com/Bale/lsbale_dop/cybernet.htm Bale, L.S. 1995, Gregory Bateson, Cybernetics and the Social/Behavioral Sciences
  3. ^ Ferguson, Adam (1767). An Essay on the History of Civil Society. London: T. Cadell. art Third, Section II, p. 205. http://oll.libertyfund.org/index.php?option=com_staticxt&staticfile=show.php%3Ftitle=1428&Itemid=28.
  4. ^ Friedrich Hayek, The Results of Human Action but Not of Human Design, in New Studies in Philosophy, Politics, Economics, Chicago: University of Chicago Press, (1978), pp. 96–105.
  5. ^ Bruce J. Caldwell, Popper and Hayek: Who influenced whom?, Karl Popper 2002 Centenary Congress, 2002.
  6. ^ Friedrich von Hayek, The Sensory Order: An Inquiry into the Foundations of Theoretical Psychology, The University of Chicago Press, 1952.
  7. ^ Kim, James S. 21c Hyper Emotional Society, Version 9. Knol. 2009 Nov 25. Available from: http://knol.google.com/k/james-s-kim/21c-hyper-emotional-society/2ycwib2vxc76q/57.
  8. ^ CSIS paper: "Organizing for a Complex World: The Way Ahead
  9. ^ Reason Magazine - The Road from Serfdom
  10. ^ Friedrich August von Hayek - Prize Lecture
  11. ^ Hayles, N. K. (1991). Chaos Bound: Orderly Disorder in Contemporary Literature and Science. Cornell University Press, Ithaca, NY.
  12. ^ Prigogine, I. (1997). The End of Certainty, The Free Press, New York.
  13. ^ a b Cilliers, P. (1998). Complexity and Postmodernism: Understanding Complex Systems, Routledge, London.
  14. ^ Per Bak (1996). How Nature Works: The Science of Self-Organized Criticality, Copernicus, New York, U.S.
  15. ^ Colander, D. (2000). The Complexity Vision and the Teaching of Economics, E. Elgar, Northampton, Massachusetts.
  16. ^ Buchanan, M.(2000). Ubiquity : Why catastrophes happen, three river press, New-York.

Further reading

External links

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Theoretical fields Chaos theory · Complex systems · Control theory · Cybernetics · Living systems · Sociotechnical systems theory · Systems biology · System dynamics · Systems ecology · Systems engineering · Systems psychology · Systems science · Systems theory
Systems scientists Russell L. Ackoff · William Ross Ashby · Béla H. Bánáthy · Gregory Bateson · Richard E. Bellman · Stafford Beer · Ludwig von Bertalanffy · Murray Bowen · Kenneth E. Boulding · C. West Churchman · George Dantzig · Heinz von Foerster · Jay Wright Forrester · George Klir · Edward Lorenz · Niklas Luhmann · Humberto Maturana · Margaret Mead · Donella Meadows · Mihajlo D. Mesarovic · James Grier Miller · Howard T. Odum · Talcott Parsons · Ilya Prigogine · Anatol Rapoport · Claude Shannon · Francisco Varela · Kevin Warwick · Norbert Wiener

Categories: Complex systems theory | Cybernetics | Systems | Systems theory | Formal sciences

 

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