Systems have operations {system operation}.
growth
Systems can start slow, grow, and then level off, in a sigmoid curve. Systems can have linear growth, at constant rate. Systems can have exponential growth, at rate that depends on current size. Systems can have second-order exponential growth, at rate that depends on current size squared. Systems can have differential growth, in which different parts have different growth rates.
newness
To have new behavior, complex systems require information from outside system.
outside influences
Complex systems protect against changes from outside by storing information about current system state, typically in templates, and replacing changed states or parts using that information.
prediction
Machines can predict variable value, then check actual value against predicted value, then adjust prediction method. Process requires information about current system state, including current variable value. Process requires information about factors affecting output value. Process requires information about goal value. Models can use varying inputs and model-parameter configurations to find output values and compare values to actual values. Machine or researcher can then adjust model.
randomness
Randomness directly relates to information. Random events can add information to system. If a random event with low probability happens, it has high information. New information masks non-random information. New information can make systems less stable.
Random nodes or events have different time and space distributions, with different noise types. Random nodes or events can have different distributions, depending on system size or time scale. Fractals can model random events with same distribution at different scales.
rates
Going from one state to another, such as returning from non-equilibrium state to equilibrium state, requires time. Systems can move from one state to another at different speeds. Systems can use internal and external rate controls. Systems have time scales.
representations
In complex systems, several configurations and parts can typically perform same function or hold same representation. Redundancy causes some paths and functions to be equivalent. The same output can result from different processing paths.
rules
Systems have rules, exceptions to rules, checks, and balances.
symbols
System only recognize and use inside symbols. Systems cannot use symbols from outside system. Outside symbols must translate into inside symbols. Systems have mechanisms or filters to receive outside data, extract outside symbols, and translate them to inside symbols.
time
Systems and networks require time controller to coordinate data flows.
Mathematical Sciences>Computer Science>System Analysis>Operation
3-Computer Science-System Analysis-Operation
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Date Modified: 2022.0224