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An Action Planning Module Based on Vague Knowledge Extracted from Past Experiences

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4253))

Abstract

In this paper, an agent architecture is presented and a formal model for a preference choice module and planning module based on vague knowledge is described. An agent situated in an environment gathers information about objects placed around it and stores this information inside it’s own database. According to it’s preferences, an agent plans it’s actions in order to change surrounding environment into it’s preferences. Because of a partial lack of knowledge about an environment, an agent chooses a plan with a highest success ratio due to it’s previous observations.

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Author information

Authors and Affiliations

  1. Institute of Information Science and Engineering, Wrocław University of Technology, 50-370, Wrocław, Janiszewskiego 11/17, Poland

    Grzegorz Popek

Authors
  1. Grzegorz Popek
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Editor information

Editors and Affiliations

  1. School of Design, Engineering and Computing, Bournemouth University, UK

    Bogdan Gabrys

  2. Centre for SMART Systems, School of Environment and Technology, University of Brighton, BN2 4GJ, 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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© 2006 Springer-Verlag Berlin Heidelberg

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Popek, G. (2006). An Action Planning Module Based on Vague Knowledge Extracted from Past Experiences. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893011_126

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  • DOI: https://doi.org/10.1007/11893011_126

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46542-3

  • Online ISBN: 978-3-540-46544-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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