2005 AProbabilisticLanguagebasedUpon

• (Park et al., 2005) ⇒ Sungwoo Park, Frank Pfenning, and Sebastian Thrun. (2005). “A Probabilistic Language based Upon Sampling Functions.” In: Proceedings of the 32nd ACM SIGPLAN-SIGACT symposium on Principles of programming languages. ISBN:1-58113-830-X doi:10.1145/1047659.1040320

Subject Headings: Probabilistic Lambda Calculus, Probabilistic Programming Language.

Cited By

• http://scholar.google.com/scholar?q=%222005%22+A+Probabilistic+Language+based+Upon+Sampling+Functions
• http://dl.acm.org/citation.cfm?id=1047659.1040320&preflayout=flat#citedby

Quotes

Abstract

As probabilistic computations play an increasing role in solving various problems, researchers have designed probabilistic languages that treat probability distributions as primitive datatypes. Most probabilistic languages, however, focus only on discrete distributions and have limited expressive power. In this paper, we present a probabilistic language, called [math]\displaystyle{ \lambda_\circ }[/math], which uniformly supports all kinds of probability distributions -- discrete distributions, continuous distributions, and even those belonging to neither group. Its mathematical basis is sampling functions, i.e., mappings from the unit interval (0.0, 1.0] to probability domains. We also briefly describe the implementation of [math]\displaystyle{ \lambda_\circ }[/math] as an extension of Objective CAML and demonstrate its practicality with three applications in robotics: robot localization, people tracking, and robotic mapping. All experiments have been carried out with real robots.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2005 AProbabilisticLanguagebasedUpon	Sebastian Thrun Sungwoo Park Frank Pfenning			A Probabilistic Language based Upon Sampling Functions				10.1145/1047659.1040320		2005