Skip to main content

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 14))

  • 253 Accesses

Abstract

The three fundamental formal differences between the BP chain set logic and the M-chain set logic are,

  1. 1.

    The BP chain set logic operates only with the three ‘pure probability values’ 0, m and 1. In contrast, the M chain set logic operates, in addition, with interval-valued probability values such as 0m, m1, and 0m1. These are used to represent ignorance in addition to uncertainty (see sect. 10.2). Ignorance is due to insufficient information supply concerning the probability distribution (in terms of the pure probability values 0, m and 1) over the universe of chains.

    Three ways in which interval-valued probabilities enter the M logic are,

    1. (a)

      In connection with IF THEN information chain sets (see item 6 of sect. 9.2.2 and especially chapter 14).

    2. (b)

      In connection with the (prolongation and) expansion of chain sets where they replace the use of Bayes postulate (see sect. 12.2).

    3. (c)

      In connection with answers to questions. These may also be interval-valued due to insufficient information supply (see sect. 10.3.3).

  2. 2.

    The BP logic operates with only one type of conjunctive updating of probabilities, namely the procedure defined in sect. 3.7.1. We call the procedure of that section ‘updating of probabilities of type 2’. It corresponds closely to the AND connective of propositional calculus. The M logic operates, in addition, with ‘type 1’ updating of probabilities (see sections 11.2, 11.3).

  3. 3.

    Every information chain set with one or more interval-valued probabilities in its probability row can be decomposed into an information chain set with several pure probability rows (see sect. 9.2.2, item 6). Due to the insufficiency of the supplied information we do not know which of these is the correct one. Conjunction with additional information supply can decrease the number of possible pure probability rows (see fig. 9.1 and fig. 11.1).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 1998 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Hisdal née Gruenwald, E. (1998). The M-Notation and Ignorance vs Uncertainty. In: Logical Structures for Representation of Knowledge and Uncertainty. Studies in Fuzziness and Soft Computing, vol 14. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1887-1_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-7908-1887-1_10

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-2458-2

  • Online ISBN: 978-3-7908-1887-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics