Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Discovery of subroutines in genetic programming
Advances in genetic programming
Advances in genetic programming
Parallel distributed genetic programming
New ideas in optimization
Proceedings of the European Conference on Genetic Programming
Linear-Tree GP and Its Comparison with Other GP Structures
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Linear-Graph GP - A New GP Structure
EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
PADO: Learning Tree Structured Algorithms for Orchestration into an Object Recognition System
PADO: Learning Tree Structured Algorithms for Orchestration into an Object Recognition System
A new crossover technique for Cartesian genetic programming
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Graph structured program evolution
Proceedings of the 9th annual conference on Genetic and evolutionary computation
The performance of a selection architecture for genetic programming
EuroGP'08 Proceedings of the 11th European conference on Genetic programming
Linear Genetic Programming
Single node genetic programming on problems with side effects
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part I
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Graph grammars for evolutionary 3D design
Genetic Programming and Evolvable Machines
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We introduce Single Node Genetic Programming (SNGP), a new graph-based model for genetic programming in which every individual in the population consists of a single program node. Function operands are other individuals, meaning that the graph structure is imposed externally on the population as a whole, rather than existing within its members. Evolution is via a hill-climbing mechanism using a single reversible operator. Experimental results indicate substantial improvements over conventional GP in terms of solution rates, efficiency and program sizes.