Chaos exists in systems all around us. Even the simplest system of cause and effect can be subject to chaos, denying us accurate predictions of its behaviour, and sometimes giving rise to astonishing structures of large-scale order. Our growing understanding of Chaos Theory is having fascinating applications in the real world - from technology to global warming, politics, human behaviour, and even gambling on the stock market. Leonard Smith
shows that we all have an intuitive understanding of chaotic systems. He uses accessible maths and physics (replacing complex equations with simple examples like pendulums, railway lines, and tossing
coins) to explain the theory, and points to numerous examples in philosophy and literature (Edgar Allen Poe, Chang-Tzu, Arthur Conan Doyle) that illuminate the problems. The beauty of fractal patterns and their relation to chaos, as well as the history of chaos, and its uses in the real world and implications for the philosophy of science are all discussed in this Very Short Introduction. ABOUT THE SERIES: The Very Short Introductions series from Oxford
University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective,
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`Leonard Smith's Chaos (part of the Oxford Very Short Introduction series) will give you the clearest (but not too painful idea) of the maths involved... There's a lot packed into this little book, and for such a technical exploration it's surprisingly readble and enjoyable - I really wanted to keep turning the pages. Smith also has some excellent words of wisdom about common misunderstandings of chaos theory... One of the best books so far in this useful
and informative series.'
1: The Emergence of Chaos
2: Exponential Growth, Nonlinearity, Common Sense
3: Chaos in Context: Determinism Randomness and Noise
4: Chaos in Mathematical Models
5: Fractals, Strange Attractors, and Dimension(s)
6: Quantifying the Dynamics of Uncertainty
7: Real numbers, Real Observations and Computers
8: Sorry, Wrong Number: Statistics and Chaos
9: Predictability: Does Chaos Constrain Our Forecasts?
10: Applied Chaos: Can We See Through Our Models?
11: Philosophy in Chaos