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Measuring the likely effectiveness of strategies

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Artificial Intelligence and Symbolic Mathematical Computation (AISMC 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1138))

Abstract

Where we have measurable attributes and multiple possible strategies within an expert system there are situations where the theory of belief functions requires refinement and explanation. Given a set of attributes for which mapping exists to a topology of strategies, I will show how we refine Dempster-Shafer theory to interpret both combinations of strategies based on qualitative measures and combinations of possibly conflicting quantitative measures. This is then applied in an expert system for selecting appropriate numerical routines for the solution of a range of mathematical problems.

The project “More Intelligent Delivery of Numerical Analysis to a Wider Audience” is funded by the UK Govt. Joint Information Systems Committee under their New Technologies Initiative (NTI-24)

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Author information

Authors and Affiliations

  1. School of Mathematical Sciences University of Bath, Claverton Down, BA2 7AY, Bath, UK

    Brian J. Dupée

Authors
  1. Brian J. Dupée
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Editor information

Jacques Calmet John A. Campbell Jochen Pfalzgraf

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© 1996 Springer-Verlag Berlin Heidelberg

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Dupée, B.J. (1996). Measuring the likely effectiveness of strategies. In: Calmet, J., Campbell, J.A., Pfalzgraf, J. (eds) Artificial Intelligence and Symbolic Mathematical Computation. AISMC 1996. Lecture Notes in Computer Science, vol 1138. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61732-9_58

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  • DOI: https://doi.org/10.1007/3-540-61732-9_58

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61732-7

  • Online ISBN: 978-3-540-70740-0

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