Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 421-455 |
| Number of pages | 35 |
| Journal | Genetic Programming and Evolvable Machines |
| Volume | 6 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 1 Dec 2005 |
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Keywords
- grammar based genetic programming; logic grammars; recursive programs
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Evolving recursive programs by using adaptive grammar based genetic programming. / WONG, Man Leung.
In: Genetic Programming and Evolvable Machines, Vol. 6, No. 4, 01.12.2005, p. 421-455.Research output: Journal Publications › Journal Article (refereed) › Research › peer-review
TY - JOUR
T1 - Evolving recursive programs by using adaptive grammar based genetic programming
AU - WONG, Man Leung
PY - 2005/12/1
Y1 - 2005/12/1
N2 - Genetic programming (GP) extends traditional genetic algorithms to automatically induce computer programs. GP has been applied in a wide range of applications such as software re-engineering, electrical circuits synthesis, knowledge engineering, and data mining. One of the most important and challenging research areas in GP is the investigation of ways to successfully evolve recursive programs. A recursive program is one that calls itself either directly or indirectly through other programs. Because recursions lead to compact and general programs and provide a mechanism for reusing program code, they facilitate GP to solve larger and more complicated problems. Nevertheless, it is commonly agreed that the recursive program learning problem is very difficult for GP. In this paper, we propose techniques to tackle the difficulties in learning recursive programs. The techniques are incorporated into an adaptive Grammar Based Genetic Programming system (adaptive GBGP). A number of experiments have been performed to demonstrate that the system improves the effectiveness and efficiency in evolving recursive programs.
AB - Genetic programming (GP) extends traditional genetic algorithms to automatically induce computer programs. GP has been applied in a wide range of applications such as software re-engineering, electrical circuits synthesis, knowledge engineering, and data mining. One of the most important and challenging research areas in GP is the investigation of ways to successfully evolve recursive programs. A recursive program is one that calls itself either directly or indirectly through other programs. Because recursions lead to compact and general programs and provide a mechanism for reusing program code, they facilitate GP to solve larger and more complicated problems. Nevertheless, it is commonly agreed that the recursive program learning problem is very difficult for GP. In this paper, we propose techniques to tackle the difficulties in learning recursive programs. The techniques are incorporated into an adaptive Grammar Based Genetic Programming system (adaptive GBGP). A number of experiments have been performed to demonstrate that the system improves the effectiveness and efficiency in evolving recursive programs.
KW - grammar based genetic programming; logic grammars; recursive programs
UR - http://commons.ln.edu.hk/sw_master/4090
U2 - 10.1007/s10710-005-4805-8
DO - 10.1007/s10710-005-4805-8
M3 - Journal Article (refereed)
VL - 6
SP - 421
EP - 455
JO - Genetic Programming and Evolvable Machines
JF - Genetic Programming and Evolvable Machines
SN - 1389-2576
IS - 4
ER -