A Conditional Dependency Based Probabilistic Model Building Grammatical Evolution
Summary :
In this paper, a new approach to grammatical evolution is presented. The aim is to generate complete programs using probabilistic modeling and sampling of (probability) distribution of given grammars. To be exact, probabilistic context free grammars are employed and a modified mapping process is developed to create new individuals from the distribution of grammars. To consider problem structures in the individual generation, conditional dependencies between production rules are incorporated into the mapping process. Experiments confirm that the proposed algorithm is more effective than existing methods.
- Publication
- IEICE TRANSACTIONS on Information Vol.E99-D No.7 pp.1937-1940
- Publication Date
- 2016/07/01
- Publicized
- 2016/04/11
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2016EDL8004
- Type of Manuscript
- LETTER
- Category
- Artificial Intelligence, Data Mining
Authors
Hyun-Tae KIM
Sungkyunkwan University
Hyun-Kyu KANG
Konkuk University
Chang Wook AHN
Sungkyunkwan University
Keyword
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Hyun-Tae KIM, Hyun-Kyu KANG, Chang Wook AHN, "A Conditional Dependency Based Probabilistic Model Building Grammatical Evolution" in IEICE TRANSACTIONS on Information,
vol. E99-D, no. 7, pp. 1937-1940, July 2016, doi: 10.1587/transinf.2016EDL8004.
Abstract: In this paper, a new approach to grammatical evolution is presented. The aim is to generate complete programs using probabilistic modeling and sampling of (probability) distribution of given grammars. To be exact, probabilistic context free grammars are employed and a modified mapping process is developed to create new individuals from the distribution of grammars. To consider problem structures in the individual generation, conditional dependencies between production rules are incorporated into the mapping process. Experiments confirm that the proposed algorithm is more effective than existing methods.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2016EDL8004/_p
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@ARTICLE{e99-d_7_1937,
author={Hyun-Tae KIM, Hyun-Kyu KANG, Chang Wook AHN, },
journal={IEICE TRANSACTIONS on Information},
title={A Conditional Dependency Based Probabilistic Model Building Grammatical Evolution},
year={2016},
volume={E99-D},
number={7},
pages={1937-1940},
abstract={In this paper, a new approach to grammatical evolution is presented. The aim is to generate complete programs using probabilistic modeling and sampling of (probability) distribution of given grammars. To be exact, probabilistic context free grammars are employed and a modified mapping process is developed to create new individuals from the distribution of grammars. To consider problem structures in the individual generation, conditional dependencies between production rules are incorporated into the mapping process. Experiments confirm that the proposed algorithm is more effective than existing methods.},
keywords={},
doi={10.1587/transinf.2016EDL8004},
ISSN={1745-1361},
month={July},}
Copy
TY - JOUR
TI - A Conditional Dependency Based Probabilistic Model Building Grammatical Evolution
T2 - IEICE TRANSACTIONS on Information
SP - 1937
EP - 1940
AU - Hyun-Tae KIM
AU - Hyun-Kyu KANG
AU - Chang Wook AHN
PY - 2016
DO - 10.1587/transinf.2016EDL8004
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E99-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2016
AB - In this paper, a new approach to grammatical evolution is presented. The aim is to generate complete programs using probabilistic modeling and sampling of (probability) distribution of given grammars. To be exact, probabilistic context free grammars are employed and a modified mapping process is developed to create new individuals from the distribution of grammars. To consider problem structures in the individual generation, conditional dependencies between production rules are incorporated into the mapping process. Experiments confirm that the proposed algorithm is more effective than existing methods.
ER -
English
