Directing crossover for reduction of bloat in GP

Canadian Conference on Electrical and Computer Engineering

Volumn 2, Issue , 2002, Pages 1111-1115

  Terrio, M D ^a   Heywood, M I ^a  

^a DALHOUSIE UNIVERSITY   (Canada)

Author keywords

Code bloat; Directed crossover

Indexed keywords

COMPUTATIONAL COMPLEXITY; REGRESSION ANALYSIS; SEMANTICS; TREES (MATHEMATICS);

CODE BLOAT;

GENETIC ALGORITHMS;

EID: 0036065359     PISSN: 08407789     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. Adaptive fitness functions for dynamic growing/pruning of program trees
2. What makes a problem GP-hard? Analysis of a tunably difficult problem in genetic programming
3. Complexity compression and evolution
4. Accurate replication in genetic programming
5. Code growth, explicitly defined introns, and alternative selection schemes
6. Exploring alternative operators and search strategies in genetic programming
7. Genetic programming using a minimum description length principle
8. Evolving computer programs without subtree crossover