What enables individually simple insects like ants to act with such precision and purpose as a group? How do trillions of neurons produce something as extraordinarily complex as consciousness? In this remarkably clear and companionable book, leading complex systems scientist Melanie Mitchell provides an intimate tour of the sciences of complexity, a broad set of efforts that seek to explain how large-scale complex, organized, and adaptive behavior can emerge from simple interactions among myriad individuals. Based on her work at the Santa Fe Institute and drawing on its interdisciplinary strategies, Mitchell brings clarity to the workings of complexity across a broad range of biological, technological, and social phenomena, seeking out the general principles or laws that apply to all of them. Richly illustrated, Complexity: A Guided Tour--winner of the 2010 Phi Beta Kappa Book Award in Science--offers a wide-ranging overview of the ideas underlying complex systems science, the current research at the forefront of this field, and the prospects for its contribution to solving some of the most important scientific questions of our time.
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Melanie Mitchell is Professor of Computer Science at Portland State University and External Professor at the Santa Fe Institute.
“All theoretical models are wrong, but some are useful.” Both inevitable error and promising usefulness abound in the bold conceptual models that Mitchell surveys in exploring the nascent science of complexity. Readers will marvel at the sheer range of settings in which complex systems operate: from ant hills to the stock market, from T cells to Web searches, from disease epidemics to power outages, complexity challenges theorists’ intellectual adroitness. With refreshing clarity, Mitchell invites nonspecialists to share in these researchers’ adventures in recognizing and measuring complexity and then predicting its cascading effects. Concepts central to thermodynamics, information theory, and computer programming all come into focus in this foray into the recesses of complexity. Still, the analysis illuminates more than explanatory frameworks (such as network diagrams and genetic algorithms); piquant personalities (including Stephen Jay Gould and John von Neumann) also receive illuminating scrutiny. Though Mitchell acknowledges the doubts of skeptics, she still expresses hope that persistent complexity researchers will yet weld their disparate accomplishments into a coherent paradigm. Mind-expanding. --Bryce Christensen
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