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Commonsense-Knowledge Based Inference Engine

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Genetic and Evolutionary Computing (ICGEC 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 579))

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Abstract

Nowadays, more and more industries achieve automatic large-scale production, and also more and more robots undertake the responsibilities of domestic chores. When machines run in industries or robots work in home, they should have abilities to make judgement and abilities to learn from experience, if they want to do their jobs well. In this study, a commonsense knowledge base (CKB) and an inference engine that can support decision making with the commonsense knowledge are built. They can understand human languages, and equip with inferencing abilities, and learning abilities.

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Author information

Authors and Affiliations

  1. Hong Kong Baptist University, Kowloon, Hong Kong

    Zhengdao Peng & Jean Lai

Authors
  1. Zhengdao Peng
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  2. Jean Lai
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Corresponding author

Correspondence to Zhengdao Peng .

Editor information

Editors and Affiliations

  1. School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong, China

    Jerry Chun-Wei Lin

  2. Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fujian University of Technology, Fuzhou, Fujian, China

    Jeng-Shyang Pan

  3. School of Computer Science, Engineering and Mathematics, Flinders University, Bedford Park, South Australia, Australia

    Shu-Chuan Chu

  4. School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong, China

    Chien-Ming Chen

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© 2018 Springer Nature Singapore Pte Ltd.

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Cite this paper

Peng, Z., Lai, J. (2018). Commonsense-Knowledge Based Inference Engine. In: Lin, JW., Pan, JS., Chu, SC., Chen, CM. (eds) Genetic and Evolutionary Computing. ICGEC 2017. Advances in Intelligent Systems and Computing, vol 579. Springer, Singapore. https://doi.org/10.1007/978-981-10-6487-6_16

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  • DOI: https://doi.org/10.1007/978-981-10-6487-6_16

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6486-9

  • Online ISBN: 978-981-10-6487-6

  • eBook Packages: EngineeringEngineering (R0)

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