2008 ChurchALanguageforGenerativeMod

• (Goodman et al., 2008) ⇒ Noah D. Goodman, Vikash K. Mansinghka, Daniel M. Roy, Keith Bonawitz, and Joshua B. Tenenbaum. (2008). “Church: A Language for Generative Models.” In: Proceedings of Uncertainty in Artificial Intelligence (UAI 2008).

Subject Headings: Church Programming Language

Cited By

• http://scholar.google.com/scholar?q=%22Church%3A+A+language+for+generative+models%22+2008

Quotes

Abstract

Formal languages for probabilistic modeling enable re-use, modularity, and descriptive clarity, and can foster generic inference techniques. We introduce Church, a universal language for describing stochastic generative processes. Church is based on the Lisp model of lambda calculus, containing a pure Lisp as its deterministic subset. The semantics of Church is defined in terms of evaluation histories and conditional distributions on such histories. Church also includes a novel language construct, the stochastic memoizer, which enables simple description of many complex non-parametric models. We illustrate language features through several examples, including: a generalized Bayes net in which parameters cluster over trials, infinite PCFGs, planning by inference, and various non-parametric clustering models. Finally, we show how to implement query on any Church program, exactly and approximately, using Monte Carlo techniques.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2008 ChurchALanguageforGenerativeMod	Joshua B. Tenenbaum Noah D. Goodman Vikash K. Mansinghka Daniel M. Roy Keith Bonawitz			Church: A Language for Generative Models