Adaptive system

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The term adaptation arises mainly in the biological scope as a trial to study the relationship between the characteristics (anatomic structure, physiological processes or behavior) of living beings and their environments. Currently, in Biology, the term adaptation has a clear and concise meaning: a biological adaptation is an anatomic structure, a physiological process or a behavior's trait of an organism that has been selected by the natural evolution in such a way that this characteristic increase the probability of reproduction of an organism.

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. Feedback loops represent a key feature of adaptive systems, allowing the response to changes; examples of adaptive systems include: natural ecosystems, individual organisms, human communities, human organizations, and human families.

Some artificial systems can be adaptive as well; for instance, robots employ control systems that utilize feedback loops to sense new conditions in their environment and adapt accordingly.

Contents 1 The Law of Adaptation 2 See also 3 References 4 External links

[edit] The Law of Adaptation

 Every adaptive system converges to a state in which all kind of stimulation ceases.[1]

A formal definition of the Law of Adaptation is as follows:

Given a system S, we say that a physical event E is a stimulus for the system S if and only if the probability that the system suffers a change or be perturbed (in its elements or in its processes) when the event E occurs is strictly greater than the prior probability that S suffers a change independently of E:

Let S be an arbitrary system subject to changes in time t and let E be an arbitrary event that is a stimulus for the system S: we say that S is an adaptive system if and only if when t tends to infinity the probability that the system S change its behavior in a time step t₀ given the event E is equal to the probability that the system change its behavior independently of the occurrence of the event E. In mathematical terms:

  1- 

  2- 

Thus, for each instant t will exist a temporal interval h such that:

[edit] See also

• Adaptive immune system
• Artificial neural network
• Complex adaptive system
• Diffusion of innovations
• Ecosystems
• Neural adaptation

[edit] References

• Martin H., Jose Antonio.; Javier de Lope; Darío Maravall (2008). "Adaptation, Anticipation and Rationality in Natural and Artificial Systems: Computational Paradigms Mimicking Nature". Natural Computing (Springer) online first: 1–19. doi:10.1007/s11047-008-9096-6. 

1. ^ Martin H.

[edit] External links

• Introduction to Social Macrodynamics. Mathematical Models of the World System Development