Cycles in Bayesian networks: probabilistic semantics and relations with neighboring nodes
Abstract
We consider directed (feedback) cycles in Bayesian belief networks, taking into consideration their interaction with successors and predecessors in the network. We also consider the case of multivalued variables. Our discussion leads to the conclusion that a cycle in a BBN may by itself influence its parents, making some of their assignments inconsistent. We also consider a sufficient condition of a cycle’s consistency in an algebraic Bayesian network. If it holds, the cycle may be transformed into a linear chain of knowledge patterns of constant size. We also make numerical examples, including an example of a cycle, some assignments of whose parents turn out to be inconsistent.References
Published
2006-02-01
How to Cite
Tulupyev, Nikolenko, & Sirotkin,. (2006). Cycles in Bayesian networks: probabilistic semantics and relations with neighboring nodes. SPIIRAS Proceedings, 1(3), 240-263. https://doi.org/10.15622/sp.3.14
Section
Articles
Authors who publish with this journal agree to the following terms:
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
