Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance

Syed Imran Shafiq; Cesar Sanin; Edward Szczerbicki

doi:10.1016/j.procs.2021.09.170

Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance

Abstrakt

Machine learning and Artificial Intelligence have grown significant attention from industry and academia during the past decade. The key reason behind interest is such technologies capabilities to revolutionize human life since they seamlessly integrate classical networks, networked objects and people to create more efficient environments. In this paper, the Knowledge Representation technique of Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA) is applied to facilitate Machine Learning. For effective and efficient decision-making in Machine Learning, the environment's own experience is captured, stored and reused using the DDNA technique. The proposed approach is implemented on practical test cases like a Chatbot. Decisional DNA gathers explicit experiential knowledge based on formal decision events and uses this knowledge to support decision-making processes. The experimental test and results of the presented implementation of Decisional DNA Chatbot case studies support it as a technology that can improve and be applied to the technology, enhancing intelligence by predicting capabilities and facilitating knowledge engineering processes.

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Autorzy (3)

Syed Imran Shafiq
- University of Newcastle, Australia
Cesar Sanin
- University of Newcastle, Australia
Edward Szczerbicki prof. dr hab. inż.

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Wersja publikacji: Accepted albo Published Version
DOI:: Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1016/j.procs.2021.09.170
Licencja: otwiera się w nowej karcie

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Informacje szczegółowe

Kategoria:: Aktywność konferencyjna
Typ:: publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Opublikowano w:: Procedia Computer Science nr 192, strony 3955 - 3965,
ISSN: 1877-0509
Język:: angielski
Rok wydania:: 2021
Opis bibliograficzny:: Shafiq S. I., Sanin C., Szczerbicki E.: Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance// / : , 2021, s.3955-3965
DOI:: Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1016/j.procs.2021.09.170
Weryfikacja:: Politechnika Gdańska