Complexity: A Guided TourWhat 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. |
Contents
Life and Evolution in Computers | 113 |
Computation Writ Large | 143 |
Network Thinking | 225 |
Conclusion | 289 |
Notes | 304 |
326 | |
337 | |
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Common terms and phrases
adaptive analogy answer ants automata Barabási behavior biologists biology body brain called cascading failure cells cellular automaton chaos chapter codelets colonies communication complex systems concepts cooperation corresponds Darwin degree distribution described Douglas Hofstadter dynamics Empty Empty Empty encode Enquist entropy evolution evolutionary evolved example exploration figure fractal genes genetic algorithm genome Gödel halt Hofstadter human idea models immune system in-degree in-links information content information processing initial configuration input interactions John von Neumann Kauffman large number letter living systems logistic map lymphocytes mathematical mathematician mechanics metabolic scaling theory microstates molecules natural selection Neumann neurons nodes notion organisms particles physicist physics players population possible power law predict Prisoner's Dilemma problem proposed proteins random RBNs real-world rightmost Robby rule scale-free networks scientific scientists self-organization self-reproducing simple simulations small-world small-world network species strategy string structure tape thermodynamics Turing machine University Wolfram York