Abstract
Recently, many methods of evolutionary computation such as Genetic Algorithm(GA) and Genetic Programming(GP) have been developed as a basic tool for modeling and optimizing the complex systems. Generally speaking, GA has the genome of string structure, while the genome in GP is the tree structure. Therefore, GP is suitable to construct the complicated programs, which can be applied to many real world problems. But, GP might be sometimes difficult to search for a solution because of its bloat. In this paper, a new evolutionary method named Genetic Network Programming(GNP), whose genome is network structure is proposed to overcome the low searching efficiency of GP and is applied to the problem on the evolution of behaviors of ants in order to study the effectiveness of GNP. In addition, the comparison of the performances between GNP and GP is carried out in simulations on ants behaviors.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the IEEE Conference on Evolutionary Computation, ICEC |
| Pages | 1276-1282 |
| Number of pages | 7 |
| Volume | 2 |
| Publication status | Published - 2001 |
| Externally published | Yes |
| Event | Congress on Evolutionary Computation 2001 - Seoul Duration: 2001 May 27 → 2001 May 30 |
Other
| Other | Congress on Evolutionary Computation 2001 |
|---|---|
| City | Seoul |
| Period | 01/5/27 → 01/5/30 |
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ASJC Scopus subject areas
- Computer Science(all)
- Engineering(all)
Cite this
Comparison between Genetic Network Programming(gnp) and Genetic Programming(gp). / Hirasawa, K.; Okubo, M.; Furuzuki, Takayuki; Katagiri, H.; Murata, J.
Proceedings of the IEEE Conference on Evolutionary Computation, ICEC. Vol. 2 2001. p. 1276-1282.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Comparison between Genetic Network Programming(gnp) and Genetic Programming(gp)
AU - Hirasawa, K.
AU - Okubo, M.
AU - Furuzuki, Takayuki
AU - Katagiri, H.
AU - Murata, J.
PY - 2001
Y1 - 2001
N2 - Recently, many methods of evolutionary computation such as Genetic Algorithm(GA) and Genetic Programming(GP) have been developed as a basic tool for modeling and optimizing the complex systems. Generally speaking, GA has the genome of string structure, while the genome in GP is the tree structure. Therefore, GP is suitable to construct the complicated programs, which can be applied to many real world problems. But, GP might be sometimes difficult to search for a solution because of its bloat. In this paper, a new evolutionary method named Genetic Network Programming(GNP), whose genome is network structure is proposed to overcome the low searching efficiency of GP and is applied to the problem on the evolution of behaviors of ants in order to study the effectiveness of GNP. In addition, the comparison of the performances between GNP and GP is carried out in simulations on ants behaviors.
AB - Recently, many methods of evolutionary computation such as Genetic Algorithm(GA) and Genetic Programming(GP) have been developed as a basic tool for modeling and optimizing the complex systems. Generally speaking, GA has the genome of string structure, while the genome in GP is the tree structure. Therefore, GP is suitable to construct the complicated programs, which can be applied to many real world problems. But, GP might be sometimes difficult to search for a solution because of its bloat. In this paper, a new evolutionary method named Genetic Network Programming(GNP), whose genome is network structure is proposed to overcome the low searching efficiency of GP and is applied to the problem on the evolution of behaviors of ants in order to study the effectiveness of GNP. In addition, the comparison of the performances between GNP and GP is carried out in simulations on ants behaviors.
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M3 - Conference contribution
VL - 2
SP - 1276
EP - 1282
BT - Proceedings of the IEEE Conference on Evolutionary Computation, ICEC
ER -