Next: Initial Experiments
Up: Evolving Brick structures
Previous: Mutation and Crossover
Evolutionary Algorithm
We use a plain steady-state genetic algorithm, initialized with a population
of one single brick. Through mutation and crossover, a population of 1000 individuals
is generated and then evolved:
- 1.
- While maximum fitness < Target fitness
- 2.
- Do
- (a)
- Randomly select mutation or crossover.
- (b)
- Select 1 (for mutation) or 2 (for crossover) random individual(s) with
fitness proportional probability.
- (c)
- Apply mutation or crossover operator
- (d)
- Generate physical model and test for gravitational load
- (e)
- If the new model will support its own weight
- i.
- Then replace a random individual with it (chosen with inverse fitness
proportional probability).
Pablo Funes
2001-05-08