Using lindenmayer systems and genetic algorithms to simulate plant growth.

Plants are given a “fitness” based on their leaves -

• How much do they face the light?
• Are they too close to other leaves?
• Are they in shadow from another leaf?
• Are they below the ground?
• Also - the fitness drops as the plant description (a linenmayer system string) gets too long.

Using this measurement, a genetic algorithm can create populations of individual plants, score each one and iteratively create new populations by combining fit individuals.

The simplest strategy is to “cheat” :) Each frame is the fittest of a new population.

The result of a long run with many thousands of generations.

You can also evolve from a starting point - in this case a simple tree is modified to create a bigger and more suitable one for the environment.

Code: http://www.pawfal.org/flotsam/jetsam/patabotany/scheme/