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Knowledge-based formulation of dynamic decision models

  • Intelligent Systems
  • Conference paper
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PRICAI’98: Topics in Artificial Intelligence (PRICAI 1998)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1531))

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Abstract

We present a new methodology to automate decision making over time and uncertainty. We adopt a knowledge-based model construction approach to support automated and interactive formulation of dynamic decision models, i.e., models that explicitly consider the effects of time. Our work integrates and extends different features of the existing frameworks. We incorporate a hybrid knowledge representation scheme that integrates categorical knowledge, probabilistic knowledge, and deterministic knowledge. We provide a set of knowledge-based modification operations for automatic and interactive generation, abstraction, and refinement of the model components. We have built a knowledge base in a real-world domain and shown that it can support automated construction of a reasonable dynamic decision model. The results indicate the practical promise of the proposed design.

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Authors and Affiliations

  1. Medical Computing Laboratory, School of Computing, National University of Singapore, Lower Kent Ridge Road, 119260, Singapore

    Chenggang Wang & Tze-Yun Leong

Authors
  1. Chenggang Wang
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  2. Tze-Yun Leong
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Editor information

Hing-Yan Lee Hiroshi Motoda

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© 1998 Springer-Verlag Berlin Heidelberg

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Wang, C., Leong, TY. (1998). Knowledge-based formulation of dynamic decision models. In: Lee, HY., Motoda, H. (eds) PRICAI’98: Topics in Artificial Intelligence. PRICAI 1998. Lecture Notes in Computer Science, vol 1531. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0095296

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  • DOI: https://doi.org/10.1007/BFb0095296

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65271-7

  • Online ISBN: 978-3-540-49461-4

  • eBook Packages: Springer Book Archive

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