The algorithmic beauty of plants
The algorithmic beauty of plants
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
Three generations of automatically designed robots
Artificial Life
Measuring, enabling and comparing modularity, regularity and hierarchy in evolutionary design
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
How artificial ontogenies can retard evolution
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
Using a genetic algorithm to evolve cellular automata for 2D/3D computational development
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Evolving modular genetic regulatory networks
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Learning General Solutions through Multiple Evaluations during Development
ICES '08 Proceedings of the 8th international conference on Evolvable Systems: From Biology to Hardware
Automated discovery and optimization of large irregular tensegrity structures
Computers and Structures
Evolving 3d morphology and behavior by competition
Artificial Life
Morphological evolution of freeform robots
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Evolving heterochrony for cellular differentiation using vector field embryogeny
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Evolving CPPNs to grow three-dimensional physical structures
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Evolving complete robots with CPPN-NEAT: the utility of recurrent connections
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Robustness and the Halting Problem for Multicellular Artificial Ontogeny
IEEE Transactions on Evolutionary Computation
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In the evolution of Generative and Developmental Systems (GDS), the choice of where along the ontogenic trajectory to stop development in order to measure fitness can have a profound effect upon the emergent solutions. After illustrating the complexities of ontogenic fitness trajectories, we introduce a GDS encoding without an a priori fixed developmental duration, which instead slowly increases the duration over the course of evolution. Applied to a soft robotic locomotion task, we demonstrate how this approach can not only retain the well known advantages of developmental encodings, but also be more efficient and arrive at more parsimonious solutions than approaches with static developmental time frames.