Evolving Compact Solutions in Genetic Programming: A Case Study

  title={Evolving Compact Solutions in Genetic Programming: A Case Study},
  author={Tobias Blickle},
Genetic programming (GP) is a variant of genetic algorithms where the data structures handled are trees. This makes GP especially useful for evolving functional relationships or computer programs, as both can be represented as trees. Symbolic regression is the determination of a function dependence y = g(x) that approximates a set of data points (x i ; yi). In this paper the feasibility of symbolic regression with GP is demonstrated on two examples taken from diierent domains. Furthermore… CONTINUE READING
Highly Cited
This paper has 61 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 34 extracted citations

The identification and exploitation of dormancy in genetic programming

Genetic Programming and Evolvable Machines • 2009
View 1 Excerpt

62 Citations

Citations per Year
Semantic Scholar estimates that this publication has 62 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-4 of 4 references

Explicitly de ned intronsand destructive crossover in genetic programming

Peter Nordin, Frank Francone, Wolfgang Banzhaf

System identi cationusing structured genetic algorithms

Hitoshi Iba, Hugo de Garis

Recombination , Selection , and the Genetic Construction ofComputer Programs

Walter Alden Tackett

Similar Papers

Loading similar papers…