Result: Probabilistic space partitioning in constraint logic programming

Title:
Probabilistic space partitioning in constraint logic programming
Authors:
ANGELOPOULOS, Nicos
Source:
ASIAN 2004 : advances in computer science (higher-level decision making)Lecture notes in computer science. :48-62
Publisher Information:
Berlin: Springer, 2004.
Publication Year:
2004
Physical Description:
print, 24 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Approche probabiliste, Probabilistic approach, Enfoque probabilista, Conditionnement, Conditioning, Acondicionamiento, Inférence, Inference, Inferencia, Interrogation base donnée, Database query, Interrogación base datos, Langage probabiliste, Probabilistic language, Lenguaje probabilista, Logique probabiliste, Probabilistic logic, Modélisation, Modeling, Modelización, Programmation logique avec contrainte, Constraint logic programming, Programación lógica con restricción, Programmation logique, Logical programming, Programación lógica, Programmation stochastique, Stochastic programming, Programación estocástica
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department of Computer Science, University of York, Heslington, York, YO1 5DD, United Kingdom
ISSN:
0302-9743
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=16398384
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.16398384
Database:
PASCAL Archive

Further Information

We present a language for integrating probabilistic reasoning and logic programming. The key idea is to use constraints based techniques such as the constraints store and finite domain variables. First we show how these techniques can be used to integrate a number of probabilistic inference algorithms with logic programming. We then proceed to detail a language which effects conditioning by probabilistically partitioning the constraint store. We elucidate the kinds of reasoning effected by the introduced language by means of two well known probabilistic problems: the three prisoners and Monty Hall. In particular we show how the syntax of the language can be used to avoid the pitfalls normally associated with the two problems. An elimination algorithm for computing the probability of a query in a given store is presented.