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Detecting the Knowledge Boundary with Prudence Analysis

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AI 2008: Advances in Artificial Intelligence (AI 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5360))

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Abstract

Prudence analysis (PA) is a relatively new, practical and highly innovative approach to solving the problem of brittleness in knowledge based systems (KBS). PA is essentially an online validation approach, where as each situation or case is presented to the KBS for inferencing the result is simultaneously validated. This paper introduces a new approach to PA that analyses the structure of knowledge rather than the comparing cases with archived situations. This new approach is positively compared against earlier systems for PA, strongly indicating the viability of the approach.

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Author information

Authors and Affiliations

  1. School of Information Technology and Mathematical Sciences, University of Ballarat, Ballarat, Victoria, 7353, Australia

    Richard Dazeley

  2. School of Computing and Information Systems, University of Tasmania, Hobart, Tasmania, 7001, Australia

    Byeong-Ho Kang

Authors
  1. Richard Dazeley
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  2. Byeong-Ho Kang
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Editor information

Editors and Affiliations

  1. Wales, School of Computer Science and Engineering,, University of New South, NSW 2052, Sydney, Australia

    Wayne Wobcke

  2. School of Mathematics, Statistics and Computer Science, Victoria University of Wellington, P.O. Box 600, 6140, Wellington, New Zealand

    Mengjie Zhang

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© 2008 Springer-Verlag Berlin Heidelberg

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Dazeley, R., Kang, BH. (2008). Detecting the Knowledge Boundary with Prudence Analysis. In: Wobcke, W., Zhang, M. (eds) AI 2008: Advances in Artificial Intelligence. AI 2008. Lecture Notes in Computer Science(), vol 5360. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89378-3_49

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  • DOI: https://doi.org/10.1007/978-3-540-89378-3_49

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89377-6

  • Online ISBN: 978-3-540-89378-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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