Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Evolving programmers: the co-evolution of intelligent recombination operators
Advances in genetic programming
Self-adaptation in evolving systems
Artificial Life
Digital life behavior in the amoeba world
Artificial Life
Genetic Programming and Autoconstructive Evolution with the Push Programming Language
Genetic Programming and Evolvable Machines
Emergence of Collective Behavior in Evolving Populations of Flying Agents
Genetic Programming and Evolvable Machines
Division blocks and the open-ended evolution of development, form, and behavior
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Unwitting distributed genetic programming via asynchronous JavaScript and XML
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Emergence of collective behavior in evolving populations of flying agents
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Expressive genetic programming
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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This paper discusses the evolution of diversifying reproduction. We measured the average difference between mothers and their children, the number of species, and the degree of adaptation in evolving populations of endogenously diversifying digital organisms using the Pushpop system. The data show that the number of species in adaptive populations is higher than in nonadaptive populations, while the variance in the differences between mothers and their children is less for adaptive populations than for non-adaptive populations. In other words, in adaptive populations the species were more numerous and the diversification processes were more reliable.