Intelligence, Rationality, Learning, Anticipation and Adaptation are terms that have been and still remain in the central stage of computer science. These terms delimit their specific areas of study; nevertheless, they are so interrelated that studying them separately is an endeavor that seems little promising. In this paper, a model of study about the phenomena of Adaptation, Anticipation and Rationality as nature-inspired computational paradigms mimicking nature is proposed by means of a division, which is oriented, towards the discrimination of these terms, from the point of view of the complexity exhibited in the behavior of the systems, where these phenomena come at play. For this purpose a series of fundamental principles and hypothesis are proposed as well as some experimental results that corroborate them.
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When we speak about equilibrium in complex systems we must distinguish two kinds of equilibrium: the static equilibrium and the dynamic equilibrium. Usually this division is made for a better understanding of the mechanisms which act in living and inert entities. The main difference is that the static equilibrium can be achieved without energy consumption, while a dynamic equilibrium requires energy consumption according to the principles of thermodynamics. For this reason is it usually stated that a biological entity is in a steady-state instead of equilibrium.
According to Eq. 1 the partial derivative of the stimulus J is zero, meaning that the control variable x will stay permanently in the same value.
We mean by thought as the continuous brain’s neural activity that supports any kind of behavior, such as decision making, memory, perceptual, attentional and homeostatic processes.
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This work has been partially funded by the Spanish Ministry of Science and Technology; project DPI2006-15346-C03-02.
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Martín H., J.A., de Lope, J. & Maravall, D. Adaptation, anticipation and rationality in natural and artificial systems: computational paradigms mimicking nature. Nat Comput 8, 757 (2009). https://doi.org/10.1007/s11047-008-9096-6
- Nature-inspired paradigms