  We describe and investigate the learning capablities displayed by a
population of self-replicating segments of computer-code subject to random
mutation: the tierra environment. We find that learning is achieved through
phase transitions that adapt the population to whichever environment it
encounters, with a learning rate characterized by the environmental variables.
Our results suggest that most effective learning is achieved close to the edge
of chaos.
