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ASME Press Select Proceedings
Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17
Editor
ISBN-10:
0791802655
No. of Pages:
650
Publisher:
ASME Press
Publication date:
2007
eBook Chapter
28 Discovering Building Blocks for Human Based Genetic Algorithms
By
Takaoki Ueda
,
Takaoki Ueda
University of Illinois at Urbana Champaign
Computer Science Urbana, Illinois
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Xavier Llorà
,
Xavier Llorà
University of Illinois at Urbana Champaign
National Center for Supercomputing Applications Urbana, Illinois
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David E Goldberg
,
David E Goldberg
University of Illinois at Urbana Champaign
Illinois Genetic Algorithms Laboratory Urbana, Illinois
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Noriko Imafujiyasui
,
Noriko Imafujiyasui
University of Illinois at Urbana Champaign
Illinois Genetic Algorithms Laboratory Urbana, Illinois
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Kumara Sastry
Kumara Sastry
University of Illinois at Urbana Champaign
Illinois Genetic Algorithms Laboratory Urbana, Illinois
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Page Count:
6
-
Published:2007
Citation
Ueda, T, Llorà, X, Goldberg, DE, Imafujiyasui, N, & Sastry, K. "Discovering Building Blocks for Human Based Genetic Algorithms." Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17. Ed. Dagli, CH. ASME Press, 2007.
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The push for rapid innovation and creativity in this Internet age places a premium on effective integration of both human and computer-generated knowledge. This paper takes the first step towards designing a competent HBGA, which can enable humans to innovate quickly, reliably, and accurately. Specifically, this paper proposes a methodology for discovering building blocks from text documents including reports, chat, transcripts and e-mail. The proposed method has been applied to simple test problems and to a news article set. The results show that the proposed BB-identification methodology is effective and enables humans to effectively exchange the BBs for rapid innovation.
Abstract
1. Introduction
2. Related Research
3. Approach Overview
4. Semantic Group Identification
5. Context-Aware Semantic Building Block Identification
6. Experiments
7 Conclusions
References
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