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OVERVIEW The term ''complex adaptive systems'' (or complexity science) is often used to describe the loosely organized academic field that has grown up around the study of such systems. Complexity science is not a single theory— it encompasses more than one theoretical framework and is highly interdisciplinary, seeking the answers to some fundamental questions about living, adaptable, changeable systems. Examples of complex adaptive systems include the Stock Market , social insect and Ant colonies, the Biosphere and the Ecosystem , the Brain and the Immune System , the Cell and the developing Embryo , Manufacturing Business es and any human social group-based endeavour in a cultural and Social System such as Political Parties or Communities . There are close relationships between the field of CAS and Artificial Life . In both areas the principles Emergence and Self-organization are very important. CAS ideas and models are essentially evolutionary, grounded in modern biological views on adaptation and Evolution . The theory of complex adaptive systems bridges developments of Systems Theory with the ideas of generalized Darwinism , which suggests that Darwinian principles of evolution can explain a range of complex material phenomena, from cosmic to social objects. Definitions A CAS is a complex, self-similar collection of interacting adaptive agents. The study of CAS focuses on complex, emergent and macroscopic properties of the system. Various definitions have been offered by different researchers:
:A Complex Adaptive System (CAS) is a dynamic network of many agents (which may represent cells, species, individuals, firms, nations) acting in parallel, constantly acting and reacting to what the other agents are doing. The control of a CAS tends to be highly dispersed and decentralized. If there is to be any coherent behavior in the system, it has to arise from competition and cooperation among the agents themselves. The overall behavior of the system is the result of a huge number of decisions made every moment by many individual agents.''Complexity: The Emerging Science at the Edge of Order and Chaos'' by M. Mitchell Waldrop.
:A CAS behaves/evolves according to three key principles: order is emergent as opposed to predetermined (c.f. Neural Network s), the system's history is irreversible, and the system's future is often unpredictable. The basic building blocks of the CAS are agents. Agents scan their environment and develop schema representing interpretive and action rules. These schema are subject to change and evolution. K. Dooley, AZ State University
:Macroscopic collections of simple (and typically nonlinearly) interacting units that are endowed with the ability to evolve and adapt to a changing environment. Complexity in Social Science glossary a research training project of the European Commission General properties What distinguishes a CAS from a pure , giving them Resilience in the face of Perturbation . Other important properties are adaptation (or between agents in such a system can be analysed with Game Theory . EVOLUTION OF COMPLEXITY See Also: Evolution of complexity Living organisms are complex adaptive systems. Although complexity is hard to quantify in biology, Evolution has produced some remarkably complex organisms.1 This observation has led to the common idea of evolution being progressive and leading towards what are viewed as "higher organisms".2 If this were generally true, evolution would possess an active trend towards complexity. As shown below, in this type of process the value of the most common amount of complexity would increase over time.3 Indeed, some Artificial Life simulations have suggested that the generation of CAS is an inescapable feature of evolution.45 However, the idea of a general trend towards complexity in evolution can also be explained through a passive process. This involves an increase in Variance but the most common value, the Mode , does not change. Thus, the maximum level of complexity increases over time, but only as an indirect product of there being more organisms in total. This type of random process is also called a bounded Random Walk . In this hypothesis, the apparent trend towards more complex organisms is an illusion resulting from concentrating on the small number of large, very complex organisms that inhabit the Right-hand Tail of the complexity distribution and ignoring simpler and much more common organisms. This passive model emphasizes that the overwhelming majority of species are Microscopic Prokaryote s,6 which comprise about half the world's Biomass .7 constitute the vast majority of Earth's biodiversity.8 Therefore, simple life remains dominant on Earth, and complex life appears more diverse only because of Sampling Bias . This lack of an overall trend towards complexity in biology does not preclude the existence of forces driving systems towards complexity in a subset of cases. These minor trends are balanced by other evolutionary pressures that drive systems towards less complex states. SEE ALSO
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