Mathematical Beauty Measure
A Mathematical Beauty Measure is a beauty measure that quantifies aesthetic qualities in mathematical structures, mathematical theorems, mathematical proofs, or mathematical theories.
- AKA: Mathematical Elegance Metric, Math Aesthetic Measure.
- Context:
- It can typically quantify Mathematical Elegance through mathematical beauty criteria.
- It can typically evaluate Mathematical Simplicity through mathematical structure analysis.
- It can typically assess Mathematical Symmetry through mathematical pattern recognition.
- It can typically measure Mathematical Surprise through mathematical expectation comparison.
- It can typically characterize Mathematical Depth through mathematical insight evaluation.
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- It can often provide Mathematical Beauty Score through mathematical beauty algorithms.
- It can often compare Mathematical Solution alternatives based on their mathematical beauty characteristics.
- It can often guide Mathematical Research Direction through mathematical beauty optimization.
- It can often enhance Mathematical Education through mathematical beauty appreciation.
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- It can range from being a Simple Mathematical Beauty Measure to being a Complex Mathematical Beauty Measure, depending on its mathematical beauty dimension count.
- It can range from being a Subjective Mathematical Beauty Measure to being an Objective Mathematical Beauty Measure, depending on its mathematical beauty formalization level.
- It can range from being a Domain-Specific Mathematical Beauty Measure to being a Universal Mathematical Beauty Measure, depending on its mathematical domain applicability.
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- It can have Mathematical Beauty Component for mathematical beauty aspect evaluation.
- It can perform Mathematical Beauty Analysis for mathematical work comparison.
- It can provide Mathematical Beauty Insight for mathematical creativity enhancement.
- It can integrate with Information Theory Concept for mathematical beauty formalization.
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- It can be Mathematical Beauty Standard during mathematical community discourse.
- It can be Mathematical Beauty Benchmark for mathematical style development.
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- Examples:
- Mathematical Beauty Measure Implementations, such as:
- Proof-Based Mathematical Beauty Measures, such as:
- Algorithm-Based Mathematical Beauty Measures, such as:
- Mathematical Beauty Measure Categories, such as:
- Mathematical Beauty Measure Applications, such as:
- ...
- Mathematical Beauty Measure Implementations, such as:
- Counter-Examples:
- Musical Beauty, which evaluates aesthetic quality in sound patterns rather than mathematical structures.
- Visual Beauty, which focuses on aesthetic quality in visual forms instead of mathematical concepts.
- Beautiful Food, which concerns aesthetic quality in culinary creations rather than mathematical expressions.
- Ugly Math, which represents mathematical concepts that lack mathematical beauty despite potential mathematical correctness.
- Mathematical Rigor Measures, which focus on mathematical correctness rather than mathematical beauty.
- Mathematical Complexity Measures, which quantify mathematical difficulty without considering mathematical aesthetic quality.
- Mathematical Utility Measures, which evaluate mathematical usefulness instead of mathematical beauty.
- See: Beauty Measure, Mathematical Elegance, Mathematical Aesthetic, Mathematician, Aesthetics, Mathematics, Information Theory, Creativity.
References
2016
- (Wikipedia, 2016) ⇒ https://en.wikipedia.org/wiki/Mathematical_beauty Retrieved:2016-12-25.
- Mathematical beauty describes the notion that some mathematicians may derive aesthetic pleasure from their work, and from mathematics in general. They express this pleasure by describing mathematics (or, at least, some aspect of mathematics) as beautiful. Mathematicians describe mathematics as an art form or, at a minimum, as a creative activity. Comparisons are often made with music and poetry.
Bertrand Russell expressed his sense of mathematical beauty in these words:
Mathematics, rightly viewed, possesses not only truth, but supreme beauty — a beauty cold and austere, like that of sculpture, without appeal to any part of our weaker nature, without the gorgeous trappings of painting or music, yet sublimely pure, and capable of a stern perfection such as only the greatest art can show. The true spirit of delight, the exaltation, the sense of being more than Man, which is the touchstone of the highest excellence, is to be found in mathematics as surely as poetry.
- Mathematical beauty describes the notion that some mathematicians may derive aesthetic pleasure from their work, and from mathematics in general. They express this pleasure by describing mathematics (or, at least, some aspect of mathematics) as beautiful. Mathematicians describe mathematics as an art form or, at a minimum, as a creative activity. Comparisons are often made with music and poetry.
2016
- (Wikipedia, 2016) ⇒ https://en.wikipedia.org/wiki/Mathematical_beauty#Beauty_and_mathematical_information_theory Retrieved:2016-12-25.
- In the 1970s, Abraham Moles and Frieder Nake analyzed links between beauty, information processing, and information theory. [1] [2] In the 1990s, Jürgen Schmidhuber formulated a mathematical theory of observer-dependent subjective beauty based on algorithmic information theory: the most beautiful objects among subjectively comparable objects have short algorithmic descriptions (i.e., Kolmogorov complexity) relative to what the observer already knows. [3] [4] [5] Schmidhuber explicitly distinguishes between beautiful and interesting. The latter corresponds to the first derivative of subjectively perceived beauty: the 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 (possibly a predictive artificial neural network) 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 compression progress, and is proportional to the observer's internal curiosity reward. [6] [7]
- ↑ A. Moles: Théorie de l'information et perception esthétique, Paris, Denoël, 1973 (Information Theory and aesthetical perception)
- ↑ F Nake (1974). Ästhetik als Informationsverarbeitung. (Aesthetics as information processing). Grundlagen und Anwendungen der Informatik im Bereich ästhetischer Produktion und Kritik. Springer, 1974, ISBN 3-211-81216-4, ISBN 978-3-211-81216-7
- ↑ J. Schmidhuber. Low-complexity art. Leonardo, Journal of the International Society for the Arts, Sciences, and Technology, 30(2):97–103, 1997. http://www.jstor.org/pss/1576418
- ↑ J. Schmidhuber. Papers on the theory of beauty and low-complexity art since 1994: http://www.idsia.ch/~juergen/beauty.html
- ↑ J. Schmidhuber. Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity. Proc. 10th Intl. Conf. on Discovery Science (DS 2007) p. 26-38, LNAI 4755, Springer, 2007. Also in Proc. 18th Intl. Conf. on Algorithmic Learning Theory (ALT 2007) p. 32, LNAI 4754, Springer, 2007. Joint invited lecture for DS 2007 and ALT 2007, Sendai, Japan, 2007. http://arxiv.org/abs/0709.0674
- ↑ .J. Schmidhuber. Curious model-building control systems. International Joint Conference on Neural Networks, Singapore, vol 2, 1458–1463. IEEE press, 1991
- ↑ Schmidhuber's theory of beauty and curiosity in a German TV show: http://www.br-online.de/bayerisches-fernsehen/faszination-wissen/schoenheit--aesthetik-wahrnehmung-ID1212005092828.xml