Complexity : a guided tour
Melanie Mitchell (Author)
What enables individually simple insects like ants to act with such precision and purpose as a group? How do trillions of individual neurons produce something as extraordinarily complex as consciousness? What is it that guides self-organizing structures like the immune system, the World Wide Web, the global economy, and the human genome? These are just a few of the fascinating and elusive questions that the science of complexity seeks to answer. In this remarkably accessible and companionable book, leading complex systems scientist Melanie Mitchell provides an intimate, detailed 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. Comprehending such systems requires a wholly new approach, one that goes beyond traditional scientific reductionism and that re-maps long-standing disciplinary boundaries. 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. She explores as well the relationship between complexity and evolution, artificial intelligence, computation, genetics, information processing, and many other fields
Einfe#x1A;uhrung
xvi, 349 pages : illustrations, map ; 25 cm
9780195124415, 9780199798100, 0195124413, 0199798109
216938473
Background and history. What is complexity? ; dynamics, chaos, and prediction ; Information ; Computation ; Evolution ; Genetics, simplified ; Defining and measuring complexity
Life and evolution in computers. Self-reproducing computer programs ; Genetic algorithms
Computation writ large. Cellular automata, life, and the universe ; Computing with particles ; Information processing in living systems ; How to make analogies (if you are a computer) ; Prospects of computer modeling
Network thinking. The science of networks ; Applying network science to real-world networks ; The mystery of scaling ; Evolution, complexified
Conclusion. The past and future of the sciences of complexity
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