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Cellular automata.

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Presentation on theme: "Cellular automata."— Presentation transcript:

1 Cellular automata

2 Cellular automata An example rule set
8 possible ways to set upper patterns (23) 256 possible rule sets (28) Follows Steven Wolfram’s model in a New Kind of Science (NKS)

3 Sequence of steps Time downward (one dimensional?)

4 Rule 30

5 Rule 90

6 Rule 110

7 In color Rule 30 Rule 110

8 Conway’s Game of Life

9 Conway’s Life Rules 1.Any live cell with fewer than two live neighbors dies, as if by loneliness. 2.Any live cell with more than three live neighbors dies, as if by overcrowding. 3.Any live cell with two or three live neighbors lives, unchanged, to the next generation. 4.Any dead cell with exactly three live neighbors comes to life.

10 Many different patterns
Gosper Glider Gun Diehard Acorn

11 Game of Life Many available programs Both on site and downloadable
Thousands of named figures Many that refigure infinitely Called two dimensional

12 Growth and Diminishment

13 Genetic Algorithms

14 Genetic Algorithms Definition
a computer simulation in which a population of abstract representations (called chromosomes, genotype, or genome) of candidate solutions (called individuals, creatures, or phenotypes) to an optimization problem evolves toward better solutions. Basics A genetic representation of the solution domain, A fitness function to evaluate the solution domain. Along the way crossover and mutation Fitness tests Until a solution is found that satisfies minimum criteria

15

16 Karl Sims Evolved Virtual Creatures Not an animation
Evolved objects in motion Encased in various media (water, air, etc.) With gravity

17 Evolved Virtual Creatures


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