Genetic programming (videotape): the movie
Genetic programming (videotape): the movie
The evolution of mental models
Advances in genetic programming
PADO: a new learning architecture for object recognition
Symbolic visual learning
Parallel genetic programming: a scalable implementation using the transputer network architecture
Advances in genetic programming
Accurate Replication in Genetic Programming
Proceedings of the 6th International Conference on Genetic Algorithms
Causality in Genetic Programming
Proceedings of the 6th International Conference on Genetic Algorithms
Evolving Data Structures with Genetic Programming
Proceedings of the 6th International Conference on Genetic Algorithms
Complexity Compression and Evolution
Proceedings of the 6th International Conference on Genetic Algorithms
Evolutive Introns: A Non-Costly Method of Using Introns in GP
Genetic Programming and Evolvable Machines
Introducing Start Expression Genes to the Linkage Learning Genetic Algorithm
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Modification point depth and genome growth in genetic programming
Evolutionary Computation
Convergence Time for the Linkage Learning Genetic Algorithm
Evolutionary Computation
Eliminating Introns in Ant Colony Programming
Fundamenta Informaticae
Best SubTree genetic programming
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Code growth, explicitly defined introns, and alternative selection schemes
Evolutionary Computation
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Genetic Programming and Evolvable Machines
Multi Niche parallel GP with a junk-code migration model
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
Eliminating Introns in Ant Colony Programming
Fundamenta Informaticae
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The standard method of obtaining a response in tree-based genetic programming is to take the value returned by the root node. In non-tree representations, alternate methods have been explored. One alternative is to treat a specific location in indexed memory as the response value when the program terminates. The purpose of this paper is to explore the applicability of this technique to tree-structured programs and to explore the intron effects that these studies bring to light. This paper's experimental results support the finding that this memory-based program response technique is an improvement for some, but not all, problems. In addition, this paper's experimental results support the finding that, contrary to past research and speculation, the addition or even facilitation of introns can seriously degrade the search performance of genetic programming.