Complexity_ A Guided Tour - Melanie Mitchell [180]
Nowak, Martin, 219–223
nucleotides, 90–93, 96, 122, 275
Occam’s Razor, 99–100
onset of chaos, 35–36
Origins of Order, The (Stuart Kauffman), 285–286
out-links, 240
Packard, Norman, 160–161, 293
Pagels, Heinz, 1, 101
PageRank algorithm, 240, 244
parallel terraced scan, 182–183, 195–197
particles (in cellular automata), 166–168, 171–172
path length (network), 237–239, 245, 257, 318
pathogens, 8, 172–176, 180, 182, 195
effect on gene transcription and regulation, 249
representation of population of, 180
pathways, metabolic. See metabolic pathways
payoff matrix, 214–215
Peak, David, 168
Pepper, John, 287
period doubling route to chaos, 34–35
perpetual motion machine, 43
phenotype, 82, 90, 276
of strategy evolved by genetic algorithm, 136
pheromones, 177–181, 183–184, 195
Pierce, John, 55
Pitts, Walter, 296–297
Plato, 77
Poincaré, Henri, 21–22
population genetics, 82
power law
definition of, 245
degree distribution of the Web as a, 240–245
on double logarithmic (log-log) plot, 261
in metabolic networks, 249
in metabolic scaling, 260–266
origin of, 252
quarter-power scaling laws as, 262
relationship to fractals, 264–265
skepticism about, 253–255
Zipf’s law as, 270–272
See also scale-free distribution
pre-Darwinian notions of evolution, 72–75
preferential attachment, 252–254, 257
as example of common principles in complex systems, 294
Prigogine, Ilya, 298, 303
Principle of Computational Equivalence, 156–158
as example of common principles in complex systems, 294
Prisoner’s dilemma, 213–218
adding social norms to, 218–219
adding spatial structure to, 219–220
payoff matrix for, 214–215
proof by contradiction, 66
pseudo-random number generators, 33, 98, 133, 155, 306
punctuated equilibria (theory of), 85–86, 278
purpose (in complex systems), 184, 296, 301
quantum mechanics, 20, 33, 48, 95
renormalization in, 36
role of observer in, 46
quarter-power scaling laws, 262, 267
skepticism about universality of, 268
quasi-species, 86
Rajan, Vijay, 223
random access memory (RAM), 145–146, 161
random Boolean networks (RBNs), 282–287
attractors in, 285
effect of noise on, 287
global state of, 285
as models of genetic regulatory networks, 284, 287
regimes of behavior in, 284
random genetic drift, 82–83
randomness
in ant colonies, 177
in biological metabolism, 178
complexity as mixture of order and, 98, 102, 156
in Copycat, 198, 207–208
from deterministic chaos, 33, 38, 300
as essential in adaptive information processing, 181–184, 195–196, 295, 300
evolutionary role of, 77–78, 83
in historical contingency, 85
in immune system, 174
random number generators, 33, 98, 133, 155, 306
Rapoport, Anatol, 217, 297
receptors (on lymphocytes), 8, 173–176, 181, 183
recessive allele, 80–82
recombination, 81, 83, 89, 101
in genetic algorithms, 129
reductionism, ix–x
linearity, nonlinearity, and, 23
regular network, 236–239
average path length of, 318
regulatory T cells, 176
renormalization, 36, 38
reversibility, 43
reversible computing, 46–47
ribonucleic acid. See RNA
ribosomes, 91–93, 122, 274
RNA, 86, 89–93, 122, 274–276
in genetic regulation, 278–279
noncoding, 276, 279
RNA editing, 275
RNA polymerase, 90
Robby the robot, 130–142
Rosenfield, Israel, 181
Rothman, Tony, 43
Rubner, Max, 258, 260, 266, 268
rule 110 cellular automaton, 153–157
rule 30 cellular automaton, 154–156
rules, cellular automata, 147–149
Santa Fe Institute, x, xi, 94, 156, 160, 164, 254, 264, 282, 291
Complex Systems Summer School, 94, 300
Savage, Leonard, 297
scale-free distribution, 240–245
versus bell-curve distribution, 243–245
See also power-law distribution
scale-free networks, 239–240
degree distribution of, 240–245 (see also power-law distribution)
examples of, 247–252
origin of, 252–254, 257
resilience