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Complexity_ A Guided Tour - Melanie Mitchell [174]

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Atlantic Monthly, April 1988, pp. 29–44.

Yoon, C. K. From a few genes, life’s myriad shapes. New York Times, June 26, 2007.

Yule, G. U. A mathematical theory of evolution, based on the conclusions of Dr. J. C. Willis. Philosophical Transactions of the Royal Society of London, Ser. B, 213, 1924, pp. 21–87.

Ziff, E. and Rosenfield, I. Evolving evolution. The New York Review of Books, 53(8), May 11, 2006.

Zipf, G. K. Selected Studies of the Principle of Relative Frequency in Language. Cambridge, MA: Harvard University Press, 1932.

Zuse, K. Rechnender Raum. Braunschweig: Friedrich Vieweg & Sohn, 1969. English translation: Calculating Space. Cambridge, MA: MIT Technical Translation AZT-70-164-GEMIT, Massachusetts Institute of Technology (Project MAC), 02139, February 1970.

Zykov, V. Mytilinaios, E., Adams, B., and Lipson, H. Self-reproducing machines. Nature, 435, 2005, pp. 163–164.

INDEX

adaptation, 13, 128

balance between unfocused and focused

exploration in, 183–184

challenges to centrality of, 86

Darwin’s observations of, 76–77

as expanded beyond biological realm, 300

Holland’s general principles for, 128, 184

Lamarckian, 73

in Modern Synthesis, 83, 86

as requisite of life, 116

role in Darwin’s theory, 78–79

role of information in, 146, 170

See also evolution; natural selection

Albert, Réka, 230, 252, 294

algebraic topology, 21

algorithm, 129, 145

ant-colony optimization, 184

genetic (see genetic algorithms)

PageRank, 258

pseudo-random number generation, 133, 155, 306

for Turing machine, 63

algorithmic information content, 98–99

allele, 80–82

alternative splicing, 275

amino acids, 89–92, 140, 275

analogy

between ant colonies and brains, 5

as central to intelligence, 188, 208

conceptual slippage in, 188, 191–193, 196–197, 202, 206

definition of, 187

in definition of Shannon entropy, 54

between DNA and self-copying program, 122

between effective complexity and scientific theory formation, 99

examples of, 187–188

letter-string microworld for, 190–193

as modeled by the Copycat program, 193–208

Anderson, Phillip, 234

ant colonies, 3–5, 145, 176–178, 180–184, 195, 212

information processing (or computation) in, 176–178, 179–185, 195–196

ant colony optimization algorithms, 184

antibodies, 8–9, 172, 174–175, 195

anticodons, 91–92

antigens, 173–175, 180–183, 195

Antonopoulos, Andreas, 257

Aristotle, 16–17, 113

arrow of time, 43

artificial immune systems, 184

artificial intelligence (AI), x, 55, 185, 187, 190, 208, 227, 298

artificial life, 115–116, 292, 298

Ashby, W. Ross, 296–297

Aspray, William, 297

attractors, 30, 32, 34–35, 38, 103

in random Boolean networks, 285, 287

autonomy

as requisite for life, 116

autopoiesis, 298

Axelrod, Robert, 214–219, 222–224


Bak, Per, 303

Barabási, Albert-László, 230, 232–233, 249, 252–254, 294

basal metabolic rate. See metabolic rate

base pairs. See bases (genetic)

bases (genetic), 90–93, 96, 278. See also nucleotides

Bateson, Gregory, 296–297

B cells, 9, 172–176, 195

Beagle, H.M.S., 75–76

Beinhocker, Eric, 40

bell-curve distribution, 243–244, 269

Bennett, Charles, 46–47, 100–102

bifurcation, 34–36, 38, 285, 298

bifurcation diagram, 34–36, 103

biological constraints, 85–86, 281, 287

biologically inspired computation, 184–185, 207. See also genetic algorithms

bit of information, 45, 54

Boltzmann, Ludwig, 47–51, 307

Boltzmann entropy, 50–51, 307

Bonhoeffor, Sebastian, 223

Boole, George, 283

Boolean function, 283

Boolean networks. See random Boolean networks

Box, George, 222

brain, 5–7, 125, 168

as a computer, 56, 69, 145, 158, 168

as a network, 229, 238–239, 247–248

Brillouin, Leon, 46

Brown, James, 262–267, 294, 300

Buddha, 71

Buffon, Louis Leclerk de, 72

Burks, Alice, 57

Burks, Arthur, 57, 123, 145


CA. See cellular automata

calculus, 18, 301–302

of complexity, 301–303

Calvino, Italo, 225

Carnot, Sadi,

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