Emergence: From Chaos to OrderIn Emergence, Holland demonstrates that a small number of rules of laws can generate systems of surprising complexity. Board games provide an ancient and direct example: Chess is defined by fewer than two dozen rules, but the myriad patterns that result lead to perpetual novelty and emergence. It took centuries of study to recognize certain patterns of play, such as the control of pawn formations. But once recognized, these patterns greatly enhance the possibility of winning the game. The discovery of similar patterns in other facets of our world opens the way to a deeper understanding of the complexity of life, answering such questions as: How does a fertilized egg program the development of a trillion-cell organism? How can we build human organizations that respond rapidly to change through innovation? Throughout the book, Holland compares different systems and models that exhibit emergence in the quest for common rules or laws. |
Contents
1 Before we Proceed | 1 |
2 Games and Numbers | 16 |
3 Maps Game Theory ComputerBaseil Modeling | 28 |
4 Checkers | 53 |
5 Neural Nets | 81 |
6 Toward a General Setting | 115 |
7 Constrained Generating Procedures | 125 |
8 Samuels Checkersplayer and Other Models as Cgp s | 143 |
9 Variation | 161 |
10 Levels of Description and Redution | 188 |
11Metaphor and Innovation | 202 |
12Closing | 221 |
| 249 | |
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Common terms and phrases
activity agent-based models agents array aura axon behavior billiard ball board games building blocks cell cellular automaton cgp-v cgp's Chapter checkers chess complex components computer-based models concepts configurations connections construction Conway's automaton Copycat define detail determine emer emergent phenomena exhibit emergence fanout fatigue feedforward Figure firing rate framework free input game tree genetic algorithm glider Hebb's rule id tag innovation insights interactions interconnections large number laws learning line of play look lookahead macrolaws mathematical mechanisms metaphor minimax model building move neural nets neural networks neurons nisms notation observations opponent output particles patterns perpetual novelty persistence physics pieces ahead player possible prediction pulses reverberating role saccades Samuel's checkersplayer scientific selected sequence signal simple specified square strategy string study of emergence subroutines synapses target theory threshold tile time-step tion transition function understanding valuation function weights