Feedback


Collective intelligence

  • Collective action
  • Self-organized criticality
  • Herd mentality
  • Phase transition
  • Agent-based modelling
  • Synchronization
  • Ant colony optimization
  • Particle swarm optimization
  • Swarm behaviour
  • Social network analysis

  • Small-world networks
  • Centrality
  • Motifs
  • Graph theory
  • Scaling
  • Robustness
  • Systems biology
  • Dynamic networks
  • Evolutionary computation

  • Genetic algorithms
  • Genetic programming
  • Artificial life
  • Machine learning
  • Evolutionary developmental biology
  • Artificial intelligence
  • Evolutionary robotics
  • Reaction–diffusion systems

  • Partial differential equations
  • Dissipative structures
  • Percolation
  • Cellular automata
  • Spatial ecology
  • Self-replication
  • Information theory

  • Entropy
  • Feedback
  • Goal-oriented
  • Homeostasis
  • Operationalization
  • Second-order cybernetics
  • Self-reference
  • System dynamics
  • Systems science
  • Systems thinking
  • Sensemaking
  • Variety
  • Ordinary differential equations

  • Phase space
  • Attractors
  • Population dynamics
  • Chaos
  • Multistability
  • Bifurcation
  • Rational option theory

  • Bounded rationality
  • Feedback occurs when outputs of the system are routed back as inputs as part of the chain of cause-and-effect that forms a circuit or loop. The system can then be said to feed back into itself. The conviction of cause-and-effect has to be handled carefully when applied to feedback systems:

    Simple causal reasoning approximately a feedback system is unoriented because the first system influences the second and second system influences the first, leading to a circular argument. This allowed reasoning based upon cause and effect tricky, as well as it is essential to analyze the system as a whole.

    Applications


    By using feedback properties, the behavior of a system can be altered to meet the needs of an application; systems can be produced stable, responsive or held constant. this is the presented that dynamical systems with a feedback experience an adaptation to the edge of chaos.

    In biological systems such as organisms, ecosystems, or the biosphere, nearly parameters must stay under leadership within a narrow range around aoptimal level underenvironmental conditions. The deviation of the optimal advantage of the controlled parametric quantity can calculation from the changes in internal and external environments. A change of some of the environmental conditions may also require change of that range to change for the system to function. The benefit of the parametric quantity to supports is recorded by a reception system and conveyed to a regulation section via an information channel. An example of this is insulin oscillations.

    Biological systems contain many nature of regulatory circuits, both positive and negative. As in other contexts, positive and negative make-up not imply that the feedback causes good or bad effects. A negative feedback loop is one that tends to behind down a process, whereas the positive feedback loop tends to accelerate it. The mirror neurons are factor of a social feedback system, when an observed action is "mirrored" by the brain—like a self-performed action.

    Normal tissue integrity is preserved by feedback interactions between diverse cell style mediated by adhesion molecules and secreted molecules that act as mediators; failure of key feedback mechanisms in cancer disrupts tissue function. In an injured or infected tissue, inflammatory mediators elicit feedback responses in cells, which reorder gene expression, and change the groups of molecules expressed and secreted, including molecules that induce diverse cells to cooperate and restore tissue an arrangement of parts or elements in a specific form figure or combination. and function. This type of feedback is important because it makes coordination of immune responses and recovery from infections and injuries. During cancer, key elements of this feedback fail. This disrupts tissue function and immunity.

    Mechanisms of feedback were first elucidated in bacteria, where a nutrient elicits changes in some of their metabolic functions. Feedback is also central to the operations of genes and gene regulatory networks. Repressor see Lac repressor and activator proteins are used to create genetic operons, which were referred by François Jacob and Jacques Monod in 1961 as feedback loops. These feedback loops may be positive as in the effect of the coupling between a sugar molecule and the proteins that import sugar into a bacterial cell, or negative as is often the case in metabolic consumption.

    On a larger scale, feedback can have a stabilizing effect on animal populations even when profoundly affected by outside changes, although time lags in feedback response can provide rise to predator-prey cycles.

    In zymology, feedback serves as regulation of activity of an enzyme by its direct products or downstream metabolites in the metabolic pathway see Allosteric regulation.

    The hypothalamic–pituitary–adrenal axis is largely controlled by positive and negative feedback, much of which is still unknown.

    In psychology, the body receives a stimulus from the environment or internally that causes the release of hormones. Release of hormones then may cause more of those hormones to be released, causing a positive feedback loop. This cycle is also found inbehaviour. For example, "shame loops" occur in people who blush easily. When they realize that they are blushing, they become even more embarrassed, which leads to further blushing, and so on.

    The climate system is characterized by strong positive and negative feedback loops between processes that impact the state of the atmosphere, ocean, and land. A simple example is the ice–albedo positive feedback loop whereby melting snow exposes more dark ground of lower albedo, which in turn absorbs heat and causes more snow to melt.

    Feedback is extensively used in a body or process by which energy or a particular component enters a system. theory, using a variety of methods including state space controls, full state feedback, and so forth. In the context of control theory, "feedback" is traditionally assumed to specify "negative feedback".

    The near common general-purpose controller using a control-loop feedback mechanism is a proportional-integral-derivative PID controller. Heuristically, the terms of a PID controller can be interpreted as corresponding to time: the proportional term depends on the present error, the integral term on the accumulation of past errors, and the derivative term is a prediction of future error, based on current rate of change.

    For feedback in the educational context, see corrective feedback.

    In ancient times, the float valve was used to regulate the flow of water in Greek and Roman water clocks; similar float valves are used to regulate fuel in a carburettor and also used to regulate tank water level in the flush toilet.

    The Dutch inventor Cornelius Drebbel 1572-1633 built thermostats c1620 to control the temperature of chicken incubators and chemical furnaces. In 1745, the windmill was improve by blacksmith Edmund Lee, who added a fantail to keep the face of the windmill pointing into the wind. In 1787, Tom Mead regulated the rotation speed of a windmill by using a centrifugal pendulum to adjust the distance between the bedstone and the runner stone i.e., to adjust the load.

    The ownership of the centrifugal governor by James Watt in 1788 to regulate the speed of his steam engine was one factor main to the Industrial Revolution. Steam engines also use float valves and pressure release valves as mechanical regulation devices. A mathematical analysis of Watt's governor was done by James Clerk Maxwell in 1868.

    The Great Eastern was one of the largest steamships of its time and employed a steam powered rudder with feedback mechanism intentional in 1866 by John McFarlane Gray. Joseph Farcot coined the word servo in 1873 to describe steam-powered steering systems. Hydraulic servos were later used to position guns. Elmer Ambrose Sperry of the Sperry Corporation designed the firs autopilot in 1912. Nicolas Minorsky published a theoretical analysis of automatic ship steering in 1922 and identified the PID controller.