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Implementing EGAP-Based Many-Valued Argument Model for Uncertain Knowledge

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3215))

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Abstract

We studied the many-valued argumentation frameworks. They allow agents to make arguments with self or other agents under uncertain knowledge which is to be represented in the expressive EGAP (Extended Generalized Annotated Logic Programming). In this paper, we describe the implementation of the EGAP-based multi-valued argument models. The versatility of our many-valued argument models is shown through convincing argument examples.

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References

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Author information

Authors and Affiliations

  1. Department of Information Engineering and Graduate School of Science and Technology, Niigata University, 8050, Ninocho, Ikarashi, Niigata, 950-2181, Japan

    Taro Fukumoto, Takehisa Takahashi & Hajime Sawamura

Authors
  1. Taro Fukumoto
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  2. Takehisa Takahashi
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  3. Hajime Sawamura
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Editor information

Editors and Affiliations

  1. KES International, 2nd Floor, 145-157 St John Street, EC1V 4PY, London, United Kingdom

    Mircea Gh. Negoita

  2. Centre for SMART systems Engineering Research Centre, University of Brighton, BN2 4GJ, Moulsecoomb, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, Mawson Lakes, 5095, SA, Australia

    Lakhmi C. Jain

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© 2004 Springer-Verlag Berlin Heidelberg

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Fukumoto, T., Takahashi, T., Sawamura, H. (2004). Implementing EGAP-Based Many-Valued Argument Model for Uncertain Knowledge. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3215. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30134-9_1

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  • DOI: https://doi.org/10.1007/978-3-540-30134-9_1

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23205-6

  • Online ISBN: 978-3-540-30134-9

  • eBook Packages: Springer Book Archive

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