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Virus‐evolutionary linear genetic programming
Author(s) -
Tamura Kenji,
Mutoh Atsuko,
Nakamura Tsuyoshi,
Itoh Hidenori
Publication year - 2008
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.10030
Subject(s) - genetic programming , pointer (user interface) , computer science , schema (genetic algorithms) , population , coevolution , evolutionary algorithm , artificial intelligence , genetic algorithm , host (biology) , theoretical computer science , machine learning , biology , genetics , paleontology , demography , sociology
Many kinds of evolutionary methods have been proposed. GA and GP in particular have demonstrated their effectiveness in various problems recently, and many systems have been proposed. One is Virus‐Evolutionary Genetic Algorithm (VE‐GA), and the other is Linear Genetic Programming in C (LGPC). The performance of each system has been reported. VE‐GA is the coevolution system of host individuals and virus individuals. That can spread schema effectively among the host individuals by using virus infection and virus incorporation. LGPC implements the GP by representing the individuals to one dimension as if GA. LGPC can reduce a search cost of pointer and save machine memory, and can reduce the time to implement GP programs. We have proposed that a system introduce virus individuals in LGPC, and analyzed the performance of the system on two problems. Our system can spread schema among the population, and search solution effectively. The results of computer simulation show that this system can search for solution depending on LGPC applying problem's character compared with LGPC. © 2008 Wiley Periodicals, Inc. Electron Comm Jpn, 91(1): 32– 39, 2008; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10030