Chinese art has a long history of varied styles and emphases. Confucius emphasized the role of the arts and humanities (especially music and poetry) in broadening human nature and aiding li (etiquette, the rites) in bringing us back to what is essential about humanity. His opponent Mozi, however, argued that music and fine arts were classist and wasteful, benefiting the rich over the poor.
By the 4th century AD artists had started debating in writing over the proper goals of art as well. Gu Kaizhi
has left three surviving books on the theory of painting. Several later
artists or scholars both created art and wrote about the creation of
it. Religious and philosophical influences on art were common (and
diverse) but never universal.
Modern Chinese aesthetic theory took shape during the modernization
of China from Empire to republic in early 20th century. Thus thinkers
like Kant, Hegel, Marx and Heidegger have all been incorporated into
contemporary Chinese aesthetic theory, through philosophers like Li
Zehou.
The field of experimental aesthetics was founded by Gustav Theodor Fechner in the 19th century. Experimental aesthetics in these times had been characterized by a subject-based, inductive approach. The analysis of individual experience and behaviour based on experimental methods is a central part of experimental aesthetics. In particular, the perception of works of art, music, or modern items such as websitesor other IT products is studied. Experimental aesthetics is strongly oriented towards the natural sciences. Modern approaches mostly come from the fields of cognitive psychology or neuroscience (neuroaesthetics).
In the 1970s, Abraham Moles and Frieder Nake were among the first to analyze links between aesthetics, information processing, and information theory.
In the 1990s, Jürgen Schmidhuber described an algorithmic theory of beauty which takes the subjectivity
of the observer into account and postulates: among several observations
classified as comparable by a given subjective observer, the
aesthetically most pleasing one is the one with the shortest
description, given the observer's previous knowledge and his particular
method for encoding the data. This is closely related to the principles of algorithmic information theory and minimum description length. One of his examples: mathematicians enjoy simple proofs with a short description in their formal language. Another very concrete example describes an aesthetically pleasing human face whose proportions can be described by very few bits of information,drawing inspiration from less detailed 15th century proportion studies by Leonardo da Vinci and Albrecht Dürer. Schmidhuber's theory explicitly distinguishes between what's beautiful and what's interesting, stating that interestingness corresponds to the first derivative of subjectively perceived beauty. Here the premise is that any observer continually tries to improve the predictability and compressibility of the observations by discovering regularities such as repetitions and symmetries and fractal self-similarity. Whenever the observer's learning process (which may be a predictive neural network; see also Neuroesthetics) leads to improved data compression such that the observation sequence can be described by fewer bits than before, the temporary interestingness
of the data corresponds to the number of saved bits. This compression
progress is proportional to the observer's internal reward, also called
curiosity reward. A reinforcement learning algorithm is used to maximize future expected reward by learning to execute action sequences that cause additional interesting
input data with yet unknown but learnable predictability or regularity.
The principles can be implemented on artificial agents which then
exhibit a form of artificial curiosity.
Well-conducted, and with good health status.
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