Title :
Evolving computer programs without subtree crossover
Author :
Chellapilla, Kumar
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., San Diego, CA, USA
fDate :
9/1/1997 12:00:00 AM
Abstract :
An evolutionary programming procedure is used for optimizing computer programs in the form of symbolic expressions. Six tree mutation operators are proposed. Recombination operators such as crossover are not included. The viability and efficiency of the method is extensively investigated on a set of well-studied problems. The evidence indicates that the technique is not only viable but is indeed capable of evolving good computer programs. The results compare well with other evolutionary methods that rely on crossover to solve the same problems
Keywords :
automatic programming; genetic algorithms; programming theory; search problems; computer programs optimisation; evolutionary programming procedure; symbolic expressions; tree mutation operators; Computational modeling; Computer simulation; Engines; Genetic algorithms; Genetic mutations; Genetic programming; Machine learning; Simulated annealing;
Journal_Title :
Evolutionary Computation, IEEE Transactions on
DOI :
10.1109/4235.661552