Complex System
Jump to navigation
Jump to search
A Complex System is a non-linear dynamic system whose behavior is difficult to predict even once its individual components are well-understood.
- AKA: Complex Dynamical System, Self-Organizing System, Emergent System, Complexity-Generating System.
- Context:
- It can typically display emergent properties through component interactions that create system-level behaviors.
- It can typically exhibit Feedback Loops where system outputs influence future states.
- It can typically demonstrate Self-Organization through local interactions that produce global patterns.
- It can typically maintain Dynamic Equilibrium through balancing mechanisms and adapting processes.
- It can typically possess Distributed Control rather than centralized governance.
- ...
- It can often manifest Phase Transitions between different system states when critical thresholds are crossed.
- It can often display Cascading Failures where small disruptions trigger chain reactions.
- It can often generate Unpredictable Outcomes despite deterministic rules governing components.
- It can often create Scale-Free Networks with hub nodes and power-law distributions.
- It can often adapt to environmental changes through internal reorganization.
- ...
- It can range from being a Chaotic Complex System to being a Patterned Complex System, depending on its order parameters.
- It can range from being a Simple Complex System to being a Highly Complex System, depending on its component count and interaction density.
- It can range from being a Closed Complex System to being an Open Complex System, depending on its boundary permeability.
- It can range from being a Static Complex System to being an Evolutionary Complex System, depending on its adaptation capacity.
- It can range from being a Fragile Complex System to being an Anti-Fragile Complex System, depending on its response to perturbations.
- It can range from being a Deterministic Complex System to being a Stochastic Complex System, depending on its randomness level.
- It can range from being a Homogeneous Complex System to being a Heterogeneous Complex System, depending on its component diversity.
- It can range from being a Physical Complex System to being an Abstract Complex System, depending on its implementation substrate.
- ...
- It can demonstrate Non-Linear Response to input changes.
- It can exhibit Path Dependence where historical states influence future development.
- It can generate Novel Structures through spontaneous organization.
- It can involve Multi-Scale Dynamics across different time scales and space scales.
- It can display Robustness to certain perturbations while remaining vulnerable to others.
- It can contain nested hierarchies of subsystems and components.
- ...
- Examples:
- Complex System Types by implementation domain, such as:
- Natural Complex Systems, such as:
- Ecological Complex Systems, such as:
- Biological Complex Systems, such as:
- Geological Complex Systems, such as:
- Social Complex Systems, such as:
- Economic Complex Systems, such as:
- Cultural Complex Systems, such as:
- Political Complex Systems, such as:
- Technological Complex Systems, such as:
- Computational Complex Systems, such as:
- Engineering Complex Systems, such as:
- Abstract Complex Systems, such as:
- Mathematical Complex Systems, such as:
- Cellular Automaton Complex System with simple rules producing complex patterns.
- Fractal Complex System with self-similarity across scale levels.
- Simulation Complex Systems, such as:
- Mathematical Complex Systems, such as:
- Natural Complex Systems, such as:
- Complex System Types by behavior pattern, such as:
- Adaptive Complex Systems, such as:
- Immune System Complex System that learns from pathogen exposure.
- Neural Network Complex System that adjusts weights based on training data.
- Self-Organizing Complex Systems, such as:
- Adaptive Complex Systems, such as:
- ...
- Complex System Types by implementation domain, such as:
- Counter-Examples:
- Linear Systems, which lack feedback loops and maintain proportional relationships between inputs and outputs.
- Simple Mechanical Systems, such as pendulums or clocks, which follow predictable trajectorys.
- Isolated Systems with limited components and interactions that can be fully modeled.
- Centrally Controlled Systems with hierarchical command structures rather than distributed decision-making.
- Reducible Systems whose behaviors can be fully explained by analyzing components in isolation.
- Equilibrium-Only Systems that lack phase transitions and emergent properties.
- See: Complex Adaptive System, Emergence, Self-Organization, Feedback Loop, Chaos Theory, Network Theory, System Dynamics, Non-Linear Dynamics, Phase Transition, Criticality, Resilience, Robustness, Attractor, Path Dependence, Butterfly Effect.
References
2016
- (Wikipedia, 2016) ⇒ http://wikipedia.org/wiki/complex_system Retrieved:2016-4-18.
- A complex system is a system that exhibits some (and possibly all) of the following characteristics: * feedback loops; * some degree of spontaneous order; * robustness of the order; * emergent organization;
- A complex system can be also viewed as a system composed of many components which may interact with each other. In many cases it is useful to represent such a system as a network where the nodes represent the components and the links their interactions.
Examples of complex systems are Earth's global climate, the human brain, social organization, an ecosystem, a living cell, and ultimately the entire universe.
2014
- (Wikipedia, 2014) ⇒ http://en.wikipedia.org/wiki/complex_system Retrieved:2014-1-6.
- A complex system is a damped, driven system (for example, a harmonic oscillator) whose total energy exceeds the threshold for it to perform according to classical mechanics but does not reach the threshold for the system to exhibit properties according to chaos theory.
1900~
- George Bernard Shaw.
- QUOTE: for every complex problem there is simple solution that is wrong.