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Propagation Nets

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 8489)

Abstract

This paper is to introduce Propagation nets as a kind of Petri nets whose flowing objects are uncertain values. The approach is influenced by Bayesian networks (J. Pearl [10]) and probabilistic Horn abduction (D. Pool [12]). In contrast to Bayesian networks, the algorithms are not ”hidden” but part of the nets. The net structure together with a simple firing rule allows uncertain reasoning in backward and forward direction, where backward and forward direction are dual to each other in terms of a Petri net duality. Propagation nets allow to deal with several kinds of uncertainties. This is shown for probabilities, intervals and fuzzy numbers.

Keywords

  • Bayesian Network
  • Fuzzy Number
  • Interval Arithmetic
  • Horn Clause
  • Input Place

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  • DOI: 10.1007/978-3-319-07734-5_1
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Lautenbach, K. (2014). Propagation Nets. In: Ciardo, G., Kindler, E. (eds) Application and Theory of Petri Nets and Concurrency. PETRI NETS 2014. Lecture Notes in Computer Science, vol 8489. Springer, Cham. https://doi.org/10.1007/978-3-319-07734-5_1

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  • DOI: https://doi.org/10.1007/978-3-319-07734-5_1

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07733-8

  • Online ISBN: 978-3-319-07734-5

  • eBook Packages: Computer ScienceComputer Science (R0)