Complex Adaptive System

A '''Complex Adaptive System''' (CAS) is a special case of a [[Complex System|complex system]] which is also [[Adaptive_System|adaptive]], i.e. it has the ability to change and [[Adaptation|adapt itself]] to the environment. Typically it consists of a large number of interacting adaptive [[Agent|agents]]. CASs are used to understand events, objects, and processes in their relationship with each other. They are 'complex' - they are diverse and made up of multiple interconnected elements - and 'adaptive' - they have the capacity to change and learn from experience. They are systems where a lot of individual adaptive agents interact and communicate with each other: complex [[Multi-Agent System|MAS]] with adaptive agents. The agents of a CAS learn and change as they interact with each other. The name '''complex adaptive systems''' has been coined at the interdisciplinary [http://www.santafe.edu Santa Fe Institute] (SFI), by John H. Holland, Murray Gell-Mann and others.  John H. Holland is one of the inventors of evolutionary computation and [[Genetic Algorithm|genetic algorithm]]s, Nobel Prize laureate Murray Gell-Mann discovered quarks.

== Definitions ==

CAS are an attempt to find a new, unified way of thinking about nature, human social behavior, life and the universe itself. In general the term Complex Adaptive System (CAS) is simply used for every system and society that consists of a 
large number of mutually interacting [[Agent|agents]]. A CAS is a complex, often self-similar collectivity of interacting adaptive 
agents. The study of CAS focus on the [[Emergence|emergent]], [[Self-Organization|self-organizing]] and macroscopic properties of these [[Complex System|complex systems]]. Various definitions have been offered by different researchers:

*John H. Holland
:''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.'' (Source: M. Waldrop's book about "Complexity: The Emerging Science at the Edge of Order and Chaos"). According to John Holland, a complex adaptive system "can function (or continue to exist) only if it makes a continued adaptation to an environment that exhibits perpetual novelty" (see his article [http://www.santafe.edu/media/bulletin_articles/summer_fall1987v2n1.pdf Complex Adaptive Systems: A Primer]. It interacts with the environment in a game-like way to explore the environment. It occupies or exploits a [[Niche|niche]] in the environment. And there is a tradeoff between [[Exploitation_and_Exploration|exploration and exploitation]].

*Kevin Dooley
:''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.'' (Source: [http://www.eas.asu.edu/~kdooley/casopdef.html K. Dooley, AZ State University])

* Murray Gell-Mann
:''A complex adaptive system acquires information about its environment and its own interaction with that environment, identifying regularities in that information, condensing those regularities into a kind of "schema", or model, and acting in the real world on the basis of that schema.'' (Source: his book "The Quark and the Jaguar: Adventures in the Simple and the Complex", p.17)

* Stephanie Forrest
:''Complex adaptive systems (CAS) consist of many interacting and adapting components operating within an environment. Agents act on and are influenced by their local environment. There is no global control over the system. All agents are only able to influence other agents locally. Each agent is driven by simple mechanisms, typically condition-action rules, where the conditions are sensitive to the local environment.'' (Source: Forrest, 1990)

*Other definitions
:''Macroscopic collections of simple (and typically nonlinearly) interacting units that are endowed with the ability to evolve and adapt to a changing environment.'' (Source [http://www.irit.fr/COSI/glossary/fulllist.php?letter=C])

It is not surprising that there is no formal definition, 
because the term starts with "COMPLEX". Like the related 
concepts and buzzwords as [[Complexity|complexity]], [[Self-Organization|self-organization]] 
and [[Emergence|emergence]], it is hard to define in a formal way.
Like many other [[Buzzword|buzzwords]], it loses much of its 
fascination and appeal if you succeed in doing it despite all 
difficulties.

== Examples ==

CAS can be found in cogntitive psychology, artificial intelligence, 
scociology, ecology, biology, economics, and genetics.
Examples of CAS with the corresponding agents in parentheses are: 

* markets (traders)
* ecomomies (companies)
* ecosystems (organisms)
* immune systems (antibodies)
* biological cells (proteins)
* [[Social system|social systems]] (persons)
* [[Political system|political systems]] (parties)

Another example is the stock market in which adaptive agents (traders) learn day-by-day and change their actions as they go. A good example is the immune system. It starts off simple but learns how to prevent you from getting complex illnesses. Other examples of complex adaptive systems include the social insect and ant colonies, the biosphere and the [[ecosystem]], the brain, the cell and the developing embryo, manufacturing businesses and any social human group-based endeavour in a cultural and [[Social system|social system]] such as political parties or [[Social network|communities and social networks]]. There are close connections between the field of CAS and [[ALife]]. In both areas the principles [[Emergence|emergence]] and [[Self-Organization|self-organization]] are very important.

The terms '''complex adaptive systems''', '''complexity science''' or '''the sciences of complexity''' are often used to describe the loose academic field that has grown up around the study of complex adaptive systems. Complexity science is like [[Systems Theory|systems theory]] 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.

== Properties ==

As Robert Eisenstein, the former president of the SFI said in the SFI Bulletin from Winter 2004 Vol. 19 No. 1, 
"despite differences in substrate, there are common principles and mechanisms that underlie the processes by 
which nature organizes complex systems and how they behave. In other words, there is often simplicity within complexity." 
These common principles are for example universal scaling laws, similar underlying small-world or scale-free networks
in [[Complex Network|complex networks]], or similar forms of [[Emergence|emergence]], [[Co-evolution|co-evolution]] and [[Self-Organization|self-organization]].

Simon A. Levin (2002) mentions diversity, localization and [[Autonomy|autonomy]] as the
essential properties of a CAS:
# diversity and individuality of components,
# localized interactions among those components, and
# an autonomous process that uses the outcomes of those interactions to select a subset of those components for replication or enhancement.

According to Stephanie Forrest (1994), the term CAS refers to a system with 
the following properties:
* [[Multi-Agent System|Multi-Agent System]] A collection of primitive components, called "agents"
* INTERACTION Interactions among agents and between agents and their environments
* [[Emergence|Emergence]] Unanticipated global properties often result from the interactions
* [[Adaptation|Adaptation]] Agents adapt their behavior to other agents and environmental constraints
* [[Evolution|Evolution]] As a consequence, system behavior evolves over time

The essential property that distinguihes a complex adaptive system
from a merely complex one is certainly [[Adaptation|adaptation]].
Adaptive means agents or populations of agents are able to learn.
Either individual agents learn or the population learns, i.e. the
population is subject to a process of mutation and competitive 
selection. In any case, learning agents are able to modify their
rules according to their previous success in reacting to the
environment. The more successful rules are selected, whereas the less
successful rules are deleted.

== Principles and Theorems ==

A set of [[Basic_System_Theory|basic principles]] is well known.
Yet a theory, a set of [[Theorem|theorem]]s or "calculus" for 
these systems would be desirable. John H. Miller and Scott E. Page 
write in their book "Complex Adaptive Systems": "We hope that there 
is a complex systems equivalent of Newton's Laws of Motion".
Is there any?

[[Cellular Automata]] and Agent-Based Systems are commonly used 
to model and simulate CAS. Is there any calculus for their
complex combination of [[Iteration|iteration]] and interaction?
Or are they [[Computational_irreducibility|computationally irreducible]],
which means it is impossible in principle to shortcut or predict their 
behavior?

== CAS and MAS ==

What distinguishes a CAS from a pure MAS - the counterpart from computer science to a CAS - is the focus 
on top-level properties and macroscopic features like [[Self-Similarity|self-similarity]], [[Complexity|complexity]], [[Emergence|emergence]] and  [[Self-Organization|self-organization]]. A [[Multi-Agent System|multi-agent system]] (MAS) 
is simply defined as a system composed of multiple, interacting agents. In CASs, the agents as well as the system 
are adaptive: the  system is self-similar. A CAS is a complex, self-similar collectivity of interacting adaptive agents.
So there is not much difference between a CAS and a MAS in general, especially if the 
[[Multi-Agent System|multi-agent system]] (MAS) is adaptive or subject to [[Evolution|evolution]]. 

Other important properties are adaptation (sometimes also named homeostasis), communication, cooperation, specialization, spatial and temporal organization, and of course reproduction. They can be found on all levels: cells specialize,  adapt and reproduce themselves just like larger organisms do. Communication, cooperation takes place on all levels, from the agent to the system level.

==Researchers and scientists==

* [http://www.cs.unibo.it/~babaoglu/ Ozalp Babaoglu, University of Bologna]
* [http://cs.unm.edu/~forrest/ Stephanie Forrest, University of New Mexico]
* [http://www.cs.pdx.edu/~mm/index.html Melanie Mitchell,  Portland State University]

* [http://www.eeb.princeton.edu/~slevin/ Simon A. Levin, Princeton University]
* [http://www.santafe.edu John H. Holland, University of Michigan, Santa Fe Institute]
* [http://www.santafe.edu/sfi/People/mgm/ Murray Gell-Mann, Santa Fe Institute]

== Articles ==

CAS in general (John H. Holland)

* John H. Holland, [http://www.santafe.edu/media/bulletin_articles/summer_fall1987v2n1.pdf Complex Adaptive Systems: A Primer]
* John H. Holland, [http://www.the-scientist.com/article/display/54988/ Biology's Gift to a Complex World]

Ecosystems and Biospheres (Simon A. Levin, Timothy M. Lenton)

* [http://www1.cs.columbia.edu/~traub/sloan/LevinEcos.pdf Ecosystems and the Bioshpere as Complex Adaptive Systems], Simon A. Levin, 1998

* [http://www.ams.org/bull/2003-40-01/S0273-0979-02-00965-5/S0273-0979-02-00965-5.pdf Complex Adaptive Systems: Exploring the known, the unknown and the unknowable], Simon A. Levin, 2002

* [http://lgmacweb.env.uea.ac.uk/esmg/papers/LentonVanOijenReprint.pdf Gaia as a complex adaptive system]

Immune Systems and biological systems (Stephanie Forrest)

* [http://citeseer.ist.psu.edu/stephanie94modeling.html Modeling complex adaptive systems with Echo], S. Forrest and T. Jones. In Complex Systems: Mechanism of Adaptation, R.J. Stonier and X.H. Yu (eds.), Amsterdam, The Netherlands: IOS Press, pp. 3-21 (1994).

* Stephanie Forrest, "Emergent Computation: Self-organizing, collective, and cooperative phenomena in natural and artificial computing networks", Physica D 42 (1990) 1-11

== Books ==

* John H. Miller & Scott E. Page, Complex Adaptive Systems: An Introduction to Computational Models of Social Life, Princeton University Press, 2007

* M. Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos, Simon & Schuster, 1992

* John Holland, Hidden Order: How Adaptation Builds Complexity, Basic Books, 1996

* John H. Holland, Emergence: From Chaos To Order, Basic Books, 1999

more can be found in this [http://www-users.cs.york.ac.uk/susan/int/books.htm#soc list]

==External links==

* [http://www.cs.iastate.edu/~honavar/alife.isu.html CAS Group at Iowa State University]
* [http://www.casresearch.com/ CAS Research Site by Mark Voss]
* [http://www.santafe.edu Santa Fe Institute] - The Santa Fe Institute is devoted to creating a new kind of scientific research community, one emphasizing multidisciplinary collaboration in pursuit of understanding the common themes that arise in natural, artificial, and social systems. This unique scientific enterprise attempts to uncover the mechanisms that underlie the deep simplicity present in our complex world.
* [http://pespmc1.vub.ac.be/CAS.html A description] of complex adaptive systems on the [http://pespmc1.vub.ac.be/DEFAULT.html Principia Cybernetica Web] (a project that aims to develop a complete philosophy or worldview, based on the principles of evolutionary cybernetics, and supported by collaborative computer technologies)

* [http://groups.yahoo.com/group/CAS-Group/ Yahoo! CAS Group]
* [http://www.redfish.com/ RedFish Group]



[[Category:Systems]] [[Category:Complex Systems]] [[Category:Adaptive Systems]]