Evolving Teams of Predictors with Linear Genetic Programming
Genetic Programming and Evolvable Machines
Linear Genetic Programming (Genetic and Evolutionary Computation)
Linear Genetic Programming (Genetic and Evolutionary Computation)
Managing team-based problem solving with symbiotic bid-based genetic programming
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Parallel linear genetic programming
EuroGP'11 Proceedings of the 14th European conference on Genetic programming
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In usual Genetic Programming (GP) schemes, only the best programs survive from one generation to the next. This implies that useful code, that might be hidden inside introns in low fitness individuals, is often lost. In this paper, we propose a new representation borrowing from Linear GP (LGP), called PhenoGP, where solutions are coded as ordered lists of instruction blocks. The main goal of evolution is then to find the best ordering of the instruction blocks, with possible repetitions. When the fitness remains stalled, ignored instruction blocks, which have a low probability to be useful, are replaced. Experiments show that PhenoGP achieve competitive results against standard LGP.