Bayes-Ball: The Rational Pastime (for Determining Irrelevance and Requisite Information in Belief Networks and Influence Diagrams)
نویسنده
چکیده
One of the benefits of belief networks and influence diagrams is that so much knowl edge is captured in the graphical structure. In particular, statements of conditional irrel evance (or independence) can be verified in time linear in the size of the graph. To re solve a particular inference query or decision problem, only some of the possible states and probability distributions must be specified, the "requisite information." This paper presents a new, simple, and effi cient "Bayes-ball" algorithm which is well suited to both new students of belief net works and state of the art implementations. The Bayes-ball algorithm determines irrele vant sets and requisite information more ef ficiently than existing methods, and is linear in the size of the graph for belief networks and influence diagrams.
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