An adaptive system is a set of interacting or interdependent entities, real or abstract, forming an integrated whole that together are able to respond to environmental changes or changes in the interacting parts, in a way analogous to either continuous physiological homeostasis or evolutionary adaptation in biology. Feedback loops represent a key feature of adaptive systems, such as ecosystems and individual organisms; or in the human world, communities, organizations, and families.
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Artificial adaptive systems include robots with control systems that utilize negative feedback to maintain desired states.
The law of adaptation
The law of adaptation can be stated informally as:
Every adaptive system converges to a state in which all kind of stimulation ceases.
Formally, the law can be defined as follows:
Given a system
Let
- -
P t 0 ( S → S ′ | E ) > P t 0 ( S → S ′ ) > 0 - -
lim t → ∞ P t ( S → S ′ | E ) = P t ( S → S ′ )
Thus, for each instant
Benefit of self-adjusting systems
In an adaptive system, a parameter changes slowly and has no preferred value. In a self-adjusting system though, the parameter value “depends on the history of the system dynamics”. One of the most important qualities of self-adjusting systems is its “adaption to the edge of chaos” or ability to avoid chaos. Practically speaking, by heading to the edge of chaos without going further, a leader may act spontaneously yet without disaster. A March/April 2009 Complexity article further explains the self-adjusting systems used and the realistic implications. Physicists have shown that adaptation to the edge of chaos occurs in almost all systems with the feedback.
Practopoiesis
Practopoiesis, proposed as a term by one theorist, is a kind of adaptive or self-adjusting system in which autopoiesis of an organism or a cell occurs through allopoiesis among its components. The components are organized into a poietic hierarchy: one component creates another. For example, according to this proposal, in the brain this hierarchy leads to the capability of learning to learn.