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Schlagworte
- Petri-Netze (2)
- probability propagation nets (2)
- Bayes Procedures (1)
- Horn Clauses (1)
- Petri Nets (1)
- Petri net (1)
- Petrinetz (1)
- Probability (1)
- Probability propagation nets (1)
- Propagation (1)
Institut
- Fachbereich 4 (5) (entfernen)
In this paper, we demonstrate by means of two examples how to work with probability propagation nets (PPNs). The fiirst, which comes from the book by Peng and Reggia [1], is a small example of medical diagnosis. The second one comes from [2]. It is an example of operational risk and is to show how the evidence flow in PPNs gives hints to reduce high losses. In terms of Bayesian networks, both examples contain cycles which are resolved by the conditioning technique [3].
Probability propagation nets
(2007)
A class of high level Petri nets, called "probability propagation nets", is introduced which is particularly useful for modeling probability and evidence propagation. These nets themselves are well suited to represent the probabilistic Horn abduction, whereas specific foldings of them will be used for representing the flows of probabilities and likelihoods in Bayesian networks.