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A Probabilistic Theory of Designs Based on Distributions

  • Riccardo Bresciani
  • Andrew Butterfield
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7681)

Abstract

We present a theory of designs based on functions from the state space to real numbers, which we term distributions. This theory uses predicates, in the style of UTP, based on homogeneous relations between distributions, and is richer than the standard UTP theory of designs as it allows us to reason about probabilistic programs; the healthiness conditions H1–H4 of the standard theory are implicitly accounted for in the distributional theory we present. In addition we propose a Galois connection linkage between our distribution-based model of probabilistic designs, and the standard UTP model of (non-probabilistic) designs.

Keywords

Healthiness Condition Probabilistic Choice Probabilistic Program Homogeneous Relation Nondeterministic Choice 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Riccardo Bresciani
    • 1
  • Andrew Butterfield
    • 1
  1. 1.Foundations and Methods GroupTrinity College DublinDublinIreland

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