Presentation 2001/11/8
Characteristic Analysis of GA and GP in an Agent's Action Learning Problem, and the Improvement of the Performance of the Hybrid System
Takayuki NISHIMURA, Koji IWANUMA, Hidetomo NABESHIMA,
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Abstract(in English) In this research, in order to show clearly which of Genetic Algorithms and Genetic Programming is superior in search capability, the comparative experiment for both techniques is conducted using the shortest course problem with restriction as a task. Consequently, we showed Genetic Programming is robust to imperfect information and is superior in searching capability. Moreover, we consider the good point of both technique, propose the technique of integration of Genetic Algorithms and Genetic Programming and aim at the improvement of the performance of the hybrid system.
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Keyword(in English) Genetic Algorithms / Genetic Programming / Hybrid / Agent / Action Learning
Paper # AI2001-41
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Committee AI
Conference Date 2001/11/8(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Characteristic Analysis of GA and GP in an Agent's Action Learning Problem, and the Improvement of the Performance of the Hybrid System
Sub Title (in English)
Keyword(1) Genetic Algorithms
Keyword(2) Genetic Programming
Keyword(3) Hybrid
Keyword(4) Agent
Keyword(5) Action Learning
1st Author's Name Takayuki NISHIMURA
1st Author's Affiliation Graduate School of Electrical Engineering and Computer Science, Yamanashi University()
2nd Author's Name Koji IWANUMA
2nd Author's Affiliation Department of Computer Science and Media Engineering, Yamanashi University
3rd Author's Name Hidetomo NABESHIMA
3rd Author's Affiliation Department of Computer Science and Media Engineering, Yamanashi University
Date 2001/11/8
Paper # AI2001-41
Volume (vol) vol.101
Number (no) 419
Page pp.pp.-
#Pages 8
Date of Issue