2003 FirstOrderProbInfer

• (Poole, 2003) ⇒ David Poole. (2003). “First-Order Probabilistic Inference.” In: Proceedings of the 18th International Joint Conference On Artificial Intelligence. (IJCAI 2003)

Subject Headings

Cited By

~126 http://scholar.google.com/scholar?cites=4439700476063702042

Quotes

Abstract

• There have been many proposals for first-order belief networks (i.e., where we quantify over individuals) but these typically only let us reason about the individuals that we know about. There are many instances where we have to quantify over all of the individuals in a population. When we do this the population size often matters and we need to reason about all of the members of the population (but not necessarily individually). This paper presents an algorithm to reason about multiple individuals, where we may know particular facts about some of them, but want to treat the others as a group. Combining unification with variable elimination lets us reason about classes of individuals without needing to ground out the theory.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2003 FirstOrderProbInfer	David Poole			First-Order Probabilistic Inference			http://www.wv.inf.tu-dresden.de/Teaching/FOPR/SS-2004/Resources/Poole-IJCAI-2003.pdf