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Architecture --- Architecture postmoderne. --- Complexité de calcul (informatique) --- Esthétique. --- Architecture postmoderne --- Complexité de calcul (informatique) --- Esthétique
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Turing, Machines de --- Algorithmes --- Complexite de calcul (Informatique)
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"Whether we want to know the cause of a stock's price movements (in order to trade on this information), the key phrases that can alter public opinion of a candidate (in order to optimize a politician's speeches) or which genes work together to regulate a disease causing process (in order to intervene and disrupt it), many goals center on finding and using causes. Causes tell us not only that two phenomena are related, but how they are related. They allow us to make robust predictions about the future, explain the relationship between and occurrence of events, and develop effective policies for intervention. While predictions are often made successfully on the basis of associations alone, these relationships can be unstable. If we do not know why the resulting models work, we cannot predict when they will stop working. Lung cancer rates in an area may be correlated with match sales if many smokers use matches to light their cigarettes, but match sales may also be influenced by blackouts and seasonal trends (with many purchases around holidays or in winter). A spike in match sales due to a blackout will not result in the predicted spike in lung cancer rates, but without knowledge of the underlying causes we would not be able to anticipate that failure. Models based on associations can also lead to redundancies, since multiple effects of the true cause may be included as they are correlated with its occurrence. In applications to the biomedical domain, this can result in unnecessary diagnostic tests that may be invasive and expensive"--
Computational complexity. --- Complexité de calcul (Informatique) --- Computers --- Natural Language Processing. --- Complexité de calcul (Informatique) --- Complexity, Computational --- Electronic data processing --- Machine theory --- Information Technology --- Computer Science (Hardware & Networks)
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Computer science --- Machine theory. --- Computational complexity. --- Théorie des automates --- Complexité de calcul (Informatique) --- Programming --- Informatique
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Computer science --- Algorithms --- Computable functions --- Computational complexity --- Algorithmes --- Fonctions calculables --- Complexité de calcul (Informatique) --- Computational Complexity
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This book explains why complex systems research is important in understanding the structure, function and dynamics of complex natural and social phenomena. It illuminates how complex collective behavior emerges from the parts of a system, due to the interaction between the system and its environment. You will learn the basic concepts and methods of complex system research. It is shown that very different complex phenomena of nature and society can be analyzed and understood by nonlinear dynamics since many systems of very different fields, such as physics, chemistry, biology, economics, psychology and sociology etc. have similar architecture. "Complexity Explained" is not highly technical and mathematical, but teaches and uses the basic mathematical notions of dynamical system theory making the book useful for students of science majors and graduate courses, but it should be readable for a more general audience; actually for those, who ask: What complex systems really are?
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