We provide strong theoretical and experimental evidence that standard sub-tree crossover with uniform selection of crossover points pushes a population of a-ary GP trees towards a distribution of tree sizes of the form: Prn = (1 - ap)C_n^an + 1(1-p)^(a-1)n+1 p^n where n is the number of internal nodes in a tree and p is a constant. This result generalises the result previously reported in \citepoli:2001:EuroGP_exact, \citemcphee:2001:astamsbgplr, \citeRowe01, \citepoli03:ECJ_gener_schem_part_I, \citepoli03:ECJ_gener_schem_part_II for the case a = 1
This paper derives a population sizing relationship for genetic programming (GP). Following the popu...
This paper discusses and compares five major tree-generation algorithms for genetic programming, and...
In tree-based genetic programming (GP) there is a tendency for the program trees to increase in size...
We provide strong theoretical and experimental evidence that standard sub-tree crossover with unifor...
We provide strong theoretical and experimental evidence that standard sub-tree crossover with unifor...
Size fair crossover genetic operator for tree based genetic programming is described and tested. It ...
Size fair and homologous crossover genetic operators for tree based genetic programming are describe...
Size fair and homologous crossover genetic operators for tree based genetic programming are describe...
Proceeding of: 12th European Conference, EuroGP 2009, Tübingen, Germany, April 15-17In Genetic Progr...
One characteristic tendency of genetic programming is the production of considerably larger trees th...
We present a detailed analysis of the evolution of GP populations using the problem of finding a pro...
Fitness distributions (landscapes) of programs tend to a limit as they get bigger. Markov chain conv...
Abstract. In this paper we examine the effects of single node mutations on trees evolved via genetic...
Abstract. We extend our analysis of repetitive patterns found in genetic programming genomes to tree...
This paper presents an approach to solve the parsimony, or a tree size growth, problem in Genetic Pr...
This paper derives a population sizing relationship for genetic programming (GP). Following the popu...
This paper discusses and compares five major tree-generation algorithms for genetic programming, and...
In tree-based genetic programming (GP) there is a tendency for the program trees to increase in size...
We provide strong theoretical and experimental evidence that standard sub-tree crossover with unifor...
We provide strong theoretical and experimental evidence that standard sub-tree crossover with unifor...
Size fair crossover genetic operator for tree based genetic programming is described and tested. It ...
Size fair and homologous crossover genetic operators for tree based genetic programming are describe...
Size fair and homologous crossover genetic operators for tree based genetic programming are describe...
Proceeding of: 12th European Conference, EuroGP 2009, Tübingen, Germany, April 15-17In Genetic Progr...
One characteristic tendency of genetic programming is the production of considerably larger trees th...
We present a detailed analysis of the evolution of GP populations using the problem of finding a pro...
Fitness distributions (landscapes) of programs tend to a limit as they get bigger. Markov chain conv...
Abstract. In this paper we examine the effects of single node mutations on trees evolved via genetic...
Abstract. We extend our analysis of repetitive patterns found in genetic programming genomes to tree...
This paper presents an approach to solve the parsimony, or a tree size growth, problem in Genetic Pr...
This paper derives a population sizing relationship for genetic programming (GP). Following the popu...
This paper discusses and compares five major tree-generation algorithms for genetic programming, and...
In tree-based genetic programming (GP) there is a tendency for the program trees to increase in size...