Complexity_ A Guided Tour - Melanie Mitchell [182]
in alternate splicing and RNA editing, 275
in gene regulation, 278–279
noise in, 249
transfer RNA, 91–93, 122
translation (genetic), 91–93
Tresser, Charles, 38
tRNA, 91–93, 122
Turing, Alan, 60–61, 63–65, 68–70, 209
solution to the Entscheidungsproblem, 65–68
Turing machines, 60–63
as definition of definite procedures, 63–64
in definition of logical depth, 100
encoding of, 64–65
example of, 62
as example of idea model, 211
meaning of information in, 171
simulation of in Game of Life, 150
in solution to the Entscheidungsproblem, 65–68
universal (see universal Turing machine)
Turing statement, 66
two-body problem, 21
two-person game, 214
Ulam, Stanislaw, xi, 28, 149
uncertainty principle, 20
uncomputability, 60, 158
of the Halting problem, 65–68
See also noncomputable problem (or process)
unified principles. See universal principles
unimodal map, 35, 36, 38
universal computation
in cellular automata, 149–150, 156
in defining complexity, 102, 156
definition of, 149
in nature, 157–158
See also universal Turing machine
universal computer. See universal Turing machine
universal principles (of complex systems), 95, 292–295
examples of proposals for, 294–295
skepticism about, 293–295, 299
universal properties of chaotic systems, 34–38
universal Turing machine, 64–65,
as blueprint for programmable computers, 65, 69
cellular automata equivalent to, 149–150, 156
in defining complexity, 102, 156
Varela, Francisco, 298
variable (in computer program), 119
von Neumann, John, 28, 117–118, 124–127, 146, 149, 156, 209, 211–212, 294, 296–297
invention of cellular automata, 149
self-reproducing automaton, 122–124, 156
von-Neumann-style architecture, 146, 169–171, 209
Wang, Hao, 69
Watson, James, 89, 93, 274
Watts, Duncan, 230–231, 236–239, 257
Web (World Wide), 10, 12, 186
coevolution with search engines, 10
degree distribution of, 240–245, 265, 318
network structure of, 12, 229–230, 235–236, 240–245, 252–253, 265
resilience of, 245
search engines for, 239–240
West, Geoffrey, 263–267, 269, 294, 300
Wiener, Norbert, 209, 296–297
Wigner, Eugene, 125
Wilkins, Maurice, 93
Willinger, Walter, 269
Wolfram, Stephen, 102, 151–159, 168, 294, 303
work (as related to energy), 41–43, 51
in evolution, 72, 79
in Maxwell’s demon, 43–47
World Wide Web. See Web (World Wide)
Yeast Genome Project, 96
Yoon, Carol Kaesuk, 280
Young, Karl, 102–103
Yukawa, Hideki, 188
Ziff, Edward, 181
Zipf, George Kingsley, 270
Zipf’s law, 271
explanations for, 271–272
Zuse, Konrad, 159
1. Full references for all quotations are given in the notes.
1. Authors of popular-audience science books are always warned of the following rule: every equation in your book will cut the readership by one-half. I’m no exception—my editor told me this fact very clearly. I’m going to give the logistic map equation here anyway, so the half of you who would throw the book out the window if you ever encountered an equation, please skip over the next line.
Table of Contents
Preface
Acknowledgments
PART ONE Background and History
CHAPTER ONE What Is Complexity?
CHAPTER TWO Dynamics, Chaos, and Prediction
CHAPTER THREE Information
CHAPTER FOUR Computation
CHAPTER FIVE Evolution
CHAPTER SIX Genetics, Simplified
CHAPTER SEVEN Defining and Measuring Complexity
PART TWO Life and Evolution in Computers
CHAPTER EIGHT Self-Reproducing Computer Programs
CHAPTER NINE Genetic Algorithms
PART THREE Computation Writ Large
CHAPTER TEN Cellular Automata, Life, and the Universe
CHAPTER ELEVEN Computing with Particles
CHAPTER TWELVE Information Processing in Living Systems
CHAPTER THIRTEEN How to Make Analogies (if You Are a Computer)
CHAPTER FOURTEEN Prospects of Computer Modeling
PART FOUR Network Thinking
CHAPTER FIFTEEN The Science of Networks
CHAPTER SIXTEEN Applying Network Science to Real-World Networks
CHAPTER SEVENTEEN The Mystery of Scaling
CHAPTER