Hybrid Control to Achieve Flexibility and Efficiency in Blackboard-based Systems
Identifieur interne : 000579 ( Crin/Corpus ); précédent : 000578; suivant : 000580Hybrid Control to Achieve Flexibility and Efficiency in Blackboard-based Systems
Auteurs : H. Lâasri ; B. Maître ; J.-P. HatonSource :
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Abstract
Achieving flexibility and efficiency in AI-based systems depends on how knowledge is organized and controlled. Blackboard-based architectures have proved their utility and power in the development of advanced high level AI-based applications. However much of them have been built from scratch, implementing the blackboard model according to the criteria that appeared most appropriate for a particular application. Some implementations like solution-based focusing architectures were designed for sake of execution efficiency, while others like blackboard control architectures were built for flexibility. In order to achieve these two fundamental and conflicting behaviors in blackboard systems, we propose a meta-level architecture which achieves opportunism and efficiency by organizing knowledge in a hierarchical manner and by managing it by way of a hybrid problem-solver.
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" wicri:score="395">Hybrid Control to Achieve Flexibility and Efficiency in Blackboard-based Systems</title></titleStmt><publicationStmt><idno type="RBID">CRIN:laasri88d</idno><date when="1988" year="1988">1988</date><idno type="wicri:Area/Crin/Corpus">000579</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Hybrid Control to Achieve Flexibility and Efficiency in Blackboard-based Systems</title><author><name sortKey="Laasri, H" sort="Laasri, H" uniqKey="Laasri H" first="H." last="Lâasri">H. Lâasri</name></author><author><name sortKey="Maitre, B" sort="Maitre, B" uniqKey="Maitre B" first="B." last="Maître">B. Maître</name></author><author><name sortKey="Haton, J P" sort="Haton, J P" uniqKey="Haton J" first="J.-P." last="Haton">J.-P. Haton</name></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>artificial intelligence</term><term>blackboard architecture</term><term>hybrid control</term><term>multi-knowledge base systems</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en" wicri:score="3450">Achieving flexibility and efficiency in AI-based systems depends on how knowledge is organized and controlled. Blackboard-based architectures have proved their utility and power in the development of advanced high level AI-based applications. However much of them have been built from scratch, implementing the blackboard model according to the criteria that appeared most appropriate for a particular application. Some implementations like solution-based focusing architectures were designed for sake of execution efficiency, while others like blackboard control architectures were built for flexibility. In order to achieve these two fundamental and conflicting behaviors in blackboard systems, we propose a meta-level architecture which achieves opportunism and efficiency by organizing knowledge in a hierarchical manner and by managing it by way of a hybrid problem-solver.</div></front></TEI><BibTex type="inproceedings"><ref>laasri88d</ref><crinnumber>88-R-033</crinnumber><category>3</category><equipe>INCONNUE</equipe><author><e>Lâasri, H.</e><e>Maître, B.</e><e>Haton, J.-P.</e></author><title>Hybrid Control to Achieve Flexibility and Efficiency in Blackboard-based Systems</title><booktitle>{Proceedings Second Workshop on Blackboard Systems\, : AAAI 88, Saint-Paul (Minnesota, USA)}</booktitle><year>1988</year><month>aug</month><keywords><e>blackboard architecture</e><e>hybrid control</e><e>multi-knowledge base systems</e><e>artificial intelligence</e></keywords><abstract>Achieving flexibility and efficiency in AI-based systems depends on how knowledge is organized and controlled. Blackboard-based architectures have proved their utility and power in the development of advanced high level AI-based applications. However much of them have been built from scratch, implementing the blackboard model according to the criteria that appeared most appropriate for a particular application. Some implementations like solution-based focusing architectures were designed for sake of execution efficiency, while others like blackboard control architectures were built for flexibility. In order to achieve these two fundamental and conflicting behaviors in blackboard systems, we propose a meta-level architecture which achieves opportunism and efficiency by organizing knowledge in a hierarchical manner and by managing it by way of a hybrid problem-solver.</abstract></BibTex></record>Pour manipuler ce document sous Unix (Dilib)
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