CONTROLLED GENETIC PROGRAMMING SEARCH FOR SOLVING DECEPTIVE PROBLEMS Korkmaz, Emin Erkan Ph.D., Department of Computer Engineering Supervisor: Assoc. Prof. Dr. G\u7fokt\u7furk \u7f Ucoluk March 2003, 77 pages Traditional Genetic Programming randomly combines subtrees by applying crossover. There is a growing interest in methods that can control such recombination operations. In this thesis, a new approach is presented for guiding the recombination process for Genetic Programming. The method is based on extracting the global information of the promising solutions that appear during the genetic search. The aim is to use this information to control the crossover operation afterwards. A separate control module is used to process the colle...
Abstract. The genetic programming (GP) search method can often vary greatly in the quality of soluti...
Bibliography: pages 117-120.This thesis report presents the results of a study carried out to determ...
This paper provides an introduction to genetic algorithms and genetic programming and lists sources ...
Traditional genetic programming (GP) randomly combines subtrees by applying crossover. There is a gr...
Genetic programming is a metaheuristic search method that uses a population of variable-length compu...
This paper describes an approach for automatically decomposing a problem into subproblems and then a...
Abstract: Genetic programming (GP) is an automated method for creating a working computer program ...
The ultimate goal of learning algorithms is to find the best solution from a search space without te...
Introduction Genetic programming is a domain-independent problem-solving approach in which computer ...
Genetic programming is an automatic programming method that creates computer programs to satisfy a s...
The paper discusses the possibility to manage search direction in genetic algorithm crossover and mu...
The ultimate goal of learning algorithms is to find the best solution from a search space without t...
A significant challenge in genetic programming is premature convergence to local optima, which often...
Abstract: Genetic algorithms are search and optimization techniques which have their origin and insp...
Genetic Programming is an evolutionary computation technique which searches for those computer progr...
Abstract. The genetic programming (GP) search method can often vary greatly in the quality of soluti...
Bibliography: pages 117-120.This thesis report presents the results of a study carried out to determ...
This paper provides an introduction to genetic algorithms and genetic programming and lists sources ...
Traditional genetic programming (GP) randomly combines subtrees by applying crossover. There is a gr...
Genetic programming is a metaheuristic search method that uses a population of variable-length compu...
This paper describes an approach for automatically decomposing a problem into subproblems and then a...
Abstract: Genetic programming (GP) is an automated method for creating a working computer program ...
The ultimate goal of learning algorithms is to find the best solution from a search space without te...
Introduction Genetic programming is a domain-independent problem-solving approach in which computer ...
Genetic programming is an automatic programming method that creates computer programs to satisfy a s...
The paper discusses the possibility to manage search direction in genetic algorithm crossover and mu...
The ultimate goal of learning algorithms is to find the best solution from a search space without t...
A significant challenge in genetic programming is premature convergence to local optima, which often...
Abstract: Genetic algorithms are search and optimization techniques which have their origin and insp...
Genetic Programming is an evolutionary computation technique which searches for those computer progr...
Abstract. The genetic programming (GP) search method can often vary greatly in the quality of soluti...
Bibliography: pages 117-120.This thesis report presents the results of a study carried out to determ...
This paper provides an introduction to genetic algorithms and genetic programming and lists sources ...