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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Complex adaptive system | 2/3 | https://en.wikipedia.org/wiki/Complex_adaptive_system | reference | science, encyclopedia | 2026-05-05T14:35:56.468479+00:00 | kb-cron |
The number of elements is sufficiently large that conventional descriptions (e.g. a system of differential equations) are not only impractical, but cease to assist in understanding the system. Moreover, the elements interact dynamically, and the interactions can be physical or involve the exchange of information. Such interactions are rich, i.e. any element or sub-system in the system is affected by and affects several other elements or sub-systems. The interactions are non-linear: small changes in inputs, physical interactions or stimuli can cause large effects or very significant changes in outputs. Interactions are primarily but not exclusively with immediate neighbours and the nature of the influence is modulated. Any interaction can feed back onto itself directly or after a number of intervening stages. Such feedback can vary in quality. This is known as recurrency. The overall behavior of the system of elements is not predicted by the behavior of the individual elements Such systems may be open and it may be difficult or impossible to define system boundaries Complex systems operate under far from equilibrium conditions. There has to be a constant flow of energy to maintain the organization of the system Agents in the system are adaptive. They update their strategies in response to input from other agents, and the system itself. Elements in the system may be ignorant of the behaviour of the system as a whole, responding only to the information or physical stimuli available to them locally Robert Axelrod & Michael D. Cohen identify a series of key terms from a modeling perspective:
Strategy, a conditional action pattern that indicates what to do in which circumstances Artifact, a material resource that has definite location and can respond to the action of agents Agent, a collection of properties, strategies & capabilities for interacting with artifacts & other agents Population, a collection of agents, or, in some situations, collections of strategies System, a larger collection, including one or more populations of agents and possibly also artifacts Type, all the agents (or strategies) in a population that have some characteristic in common Variety, the diversity of types within a population or system Interaction pattern, the recurring regularities of contact among types within a system Space (physical), location in geographical space & time of agents and artifacts Space (conceptual), "location" in a set of categories structured so that "nearby" agents will tend to interact Selection, processes that lead to an increase or decrease in the frequency of various types of agent or strategies Success criteria or performance measures, a "score" used by an agent or designer in attributing credit in the selection of relatively successful (or unsuccessful) strategies or agents Turner and Baker synthesized the characteristics of complex adaptive systems from the literature and tested these characteristics in the context of creativity and innovation. Each of these eight characteristics had been shown to be present in the creativity and innovative processes:
Path dependent: Systems tend to be sensitive to their initial conditions. The same force might affect systems differently. Systems have a history: The future behavior of a system depends on its initial starting point and subsequent history. Non-linearity: React disproportionately to environmental perturbations. Outcomes differ from those of simple systems. Emergence: Each system's internal dynamics affect its ability to change in a manner that might be quite different from other systems. Irreducible: Irreversible process transformations cannot be reduced back to its original state. Adaptive/Adaptability: Systems that are simultaneously ordered and disordered are more adaptable and resilient. Operates between order and chaos: Adaptive tension emerges from the energy differential between the system and its environment. Self-organizing: Systems are composed of interdependency, interactions of its parts, and diversity in the system.
== Adaptation mechanisms == The organisation of a complex adaptive system rely on the use of internal models, mental models or schemas guiding the behaviors of the system. We can distinguish three levels of adaptation of a system:
Using a schema to react to changing circumstances in the environment. Changing a schema when the existing one does not lead to satisfactory outcomes. Selecting the systems using successful schemata among a population (survival of the fittest).
== Modelling and simulation == CAS are occasionally modelled by means of agent-based models and complex network-based models. Agent-based models are developed by means of various methods and tools primarily by means of first identifying the different agents inside the model. Another method of developing models for CAS involves developing complex network models by means of using interaction data of various CAS components. Models and simulations are often used to study proposed systems phenomena in large infrastructural systems, where empirical testing would be prohibitively expensive and risky. Examples include those use of applied agent-based and graph-theoretic approaches to digital supply-chain twins and anomaly detection in high-speed networks. In 2013 SpringerOpen/BioMed Central launched an online open-access journal on the topic of complex adaptive systems modelling (CASM). Publication of the journal ceased in 2020.
== Evolution of complexity ==