A probabilistic language based upon sampling functions

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 , 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

• Type: Conference
• Year: 2005
• Where: POPL
• Authors: Sungwoo Park, Frank Pfenning, Sebastian Thrun
• Keywords: Discrete Distributions, Most Probabilistic Languages, POPL 2005, Probability Distributions, Programming Languages