Self-Adaptive Java Production System and Its Application to a Learning Assistance System
Summary :
Although production systems are widely used in artificial intelligence (AI) applications, they are seen to have certain disadvantages in terms of their need for special purpose assistance software to build and execute their knowledge-bases (KB), and in the fact that they will not run on any operating system (platform dependency). Furthermore, for AI applications such as learning assistance systems, there is a strong requirement for a self-adaptive function enabling a flexible change in the service contents provided, according to the user. Against such a background, a Java based production system (JPS) featuring no requirement for special purpose assistance software and no platform dependency, is proposed. Furthermore, a new self-adaptive Java production system (A-JPS) is proposed to realize the "user adaptation" requirement mentioned above. Its key characteristic is the combination of JPS with a Causal-network (CN) for obtaining a "user profile". In addition, the execution time of the JPS was studied using several benchmark problems with the aim of comparing the effectiveness of different matching algorithms in their recognize-act cycles as well as comparing their performance to that of traditional procedural programs for different problem types. Moreover, the effectiveness of the user adaptation function of the A-JPS was studied for the case of a CN with a general DAG structure, using the experimental KB of a learning assistance system.
- Publication
- IEICE TRANSACTIONS on Information Vol.E87-D No.9 pp.2186-2194
- Publication Date
- 2004/09/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Artificial Intelligence and Cognitive Science
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Yoshitaka FUJIWARA, Shin-ichirou OKADA, Tomoki SUZUKI, Yoshiaki OHNISHI, Hideki YOSHIDA, "Self-Adaptive Java Production System and Its Application to a Learning Assistance System" in IEICE TRANSACTIONS on Information,
vol. E87-D, no. 9, pp. 2186-2194, September 2004, doi: .
Abstract: Although production systems are widely used in artificial intelligence (AI) applications, they are seen to have certain disadvantages in terms of their need for special purpose assistance software to build and execute their knowledge-bases (KB), and in the fact that they will not run on any operating system (platform dependency). Furthermore, for AI applications such as learning assistance systems, there is a strong requirement for a self-adaptive function enabling a flexible change in the service contents provided, according to the user. Against such a background, a Java based production system (JPS) featuring no requirement for special purpose assistance software and no platform dependency, is proposed. Furthermore, a new self-adaptive Java production system (A-JPS) is proposed to realize the "user adaptation" requirement mentioned above. Its key characteristic is the combination of JPS with a Causal-network (CN) for obtaining a "user profile". In addition, the execution time of the JPS was studied using several benchmark problems with the aim of comparing the effectiveness of different matching algorithms in their recognize-act cycles as well as comparing their performance to that of traditional procedural programs for different problem types. Moreover, the effectiveness of the user adaptation function of the A-JPS was studied for the case of a CN with a general DAG structure, using the experimental KB of a learning assistance system.
URL: https://global.ieice.org/en_transactions/information/10.1587/e87-d_9_2186/_p
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@ARTICLE{e87-d_9_2186,
author={Yoshitaka FUJIWARA, Shin-ichirou OKADA, Tomoki SUZUKI, Yoshiaki OHNISHI, Hideki YOSHIDA, },
journal={IEICE TRANSACTIONS on Information},
title={Self-Adaptive Java Production System and Its Application to a Learning Assistance System},
year={2004},
volume={E87-D},
number={9},
pages={2186-2194},
abstract={Although production systems are widely used in artificial intelligence (AI) applications, they are seen to have certain disadvantages in terms of their need for special purpose assistance software to build and execute their knowledge-bases (KB), and in the fact that they will not run on any operating system (platform dependency). Furthermore, for AI applications such as learning assistance systems, there is a strong requirement for a self-adaptive function enabling a flexible change in the service contents provided, according to the user. Against such a background, a Java based production system (JPS) featuring no requirement for special purpose assistance software and no platform dependency, is proposed. Furthermore, a new self-adaptive Java production system (A-JPS) is proposed to realize the "user adaptation" requirement mentioned above. Its key characteristic is the combination of JPS with a Causal-network (CN) for obtaining a "user profile". In addition, the execution time of the JPS was studied using several benchmark problems with the aim of comparing the effectiveness of different matching algorithms in their recognize-act cycles as well as comparing their performance to that of traditional procedural programs for different problem types. Moreover, the effectiveness of the user adaptation function of the A-JPS was studied for the case of a CN with a general DAG structure, using the experimental KB of a learning assistance system.},
keywords={},
doi={},
ISSN={},
month={September},}
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TY - JOUR
TI - Self-Adaptive Java Production System and Its Application to a Learning Assistance System
T2 - IEICE TRANSACTIONS on Information
SP - 2186
EP - 2194
AU - Yoshitaka FUJIWARA
AU - Shin-ichirou OKADA
AU - Tomoki SUZUKI
AU - Yoshiaki OHNISHI
AU - Hideki YOSHIDA
PY - 2004
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E87-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 2004
AB - Although production systems are widely used in artificial intelligence (AI) applications, they are seen to have certain disadvantages in terms of their need for special purpose assistance software to build and execute their knowledge-bases (KB), and in the fact that they will not run on any operating system (platform dependency). Furthermore, for AI applications such as learning assistance systems, there is a strong requirement for a self-adaptive function enabling a flexible change in the service contents provided, according to the user. Against such a background, a Java based production system (JPS) featuring no requirement for special purpose assistance software and no platform dependency, is proposed. Furthermore, a new self-adaptive Java production system (A-JPS) is proposed to realize the "user adaptation" requirement mentioned above. Its key characteristic is the combination of JPS with a Causal-network (CN) for obtaining a "user profile". In addition, the execution time of the JPS was studied using several benchmark problems with the aim of comparing the effectiveness of different matching algorithms in their recognize-act cycles as well as comparing their performance to that of traditional procedural programs for different problem types. Moreover, the effectiveness of the user adaptation function of the A-JPS was studied for the case of a CN with a general DAG structure, using the experimental KB of a learning assistance system.
ER -
English
