Title :
Semantically driven crossover in genetic programming
Author :
Beadle, Lawrence ; Johnson, Colin G.
Author_Institution :
Comput. Lab., Univ. of Kent, Canterbury
Abstract :
Crossover forms one of the core operations in genetic programming and has been the subject of many different investigations. We present a novel technique, based on semantic analysis of programs, which forces each crossover to make candidate programs take a new step in the behavioural search space. We demonstrate how this technique results in better performance and smaller solutions in two separate genetic programming experiments.
Keywords :
genetic algorithms; behavioural search space; genetic programming; semantic analysis; semantically driven crossover; Algorithm design and analysis; Boolean functions; Data structures; Genetic programming; Genetic programming; crossover; program semantics; reduced ordered binary decision diagrams;
Conference_Titel :
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1822-0
Electronic_ISBN :
978-1-4244-1823-7
DOI :
10.1109/CEC.2008.4630784