Stoss — A stochastic simulation system for Bayesian belief networks

Zhiyuan Luo; Alex Gammerman

Stoss — A stochastic simulation system for Bayesian belief networks

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

This paper describes a computational system, called STOSS (STOchastic Simulation System), using the stochastic simulation method to perform probabilistic reasoning for Bayesian belief networks. The system is then applied to an artificial example in the field of forensic science and the results are compared with the calculations obtained using the Causal Probabilistic Reasoning System (CPRS).

Original language	English
Title of host publication	Uncertainty in Knowledge Bases
Subtitle of host publication	Lecture Notes in Computer Science
Editors	Bernadette Bouchon-Meunier, Ronald R. Yager, Lotfi A. Zadeh
Publisher	Springer
Pages	97-105
Volume	521
ISBN (Electronic)	978-3-540-47580-4
ISBN (Print)	978-3-540-54346-6
Publication status	Published - 1991

Access to Document

http://link.springer.com/chapter/10.1007%2FBFb0028093

Cite this

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title = "Stoss — A stochastic simulation system for Bayesian belief networks",

abstract = "This paper describes a computational system, called STOSS (STOchastic Simulation System), using the stochastic simulation method to perform probabilistic reasoning for Bayesian belief networks. The system is then applied to an artificial example in the field of forensic science and the results are compared with the calculations obtained using the Causal Probabilistic Reasoning System (CPRS).",

author = "Zhiyuan Luo and Alex Gammerman",

year = "1991",

language = "English",

isbn = "978-3-540-54346-6",

volume = "521",

pages = "97--105",

editor = "Bouchon-Meunier, {Bernadette } and Yager, {Ronald R. } and Zadeh, { Lotfi A. }",

booktitle = "Uncertainty in Knowledge Bases",

publisher = "Springer",

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TY - CHAP

T1 - Stoss — A stochastic simulation system for Bayesian belief networks

AU - Luo, Zhiyuan

AU - Gammerman, Alex

PY - 1991

Y1 - 1991

N2 - This paper describes a computational system, called STOSS (STOchastic Simulation System), using the stochastic simulation method to perform probabilistic reasoning for Bayesian belief networks. The system is then applied to an artificial example in the field of forensic science and the results are compared with the calculations obtained using the Causal Probabilistic Reasoning System (CPRS).

AB - This paper describes a computational system, called STOSS (STOchastic Simulation System), using the stochastic simulation method to perform probabilistic reasoning for Bayesian belief networks. The system is then applied to an artificial example in the field of forensic science and the results are compared with the calculations obtained using the Causal Probabilistic Reasoning System (CPRS).

M3 - Chapter

SN - 978-3-540-54346-6

VL - 521

SP - 97

EP - 105

BT - Uncertainty in Knowledge Bases

A2 - Bouchon-Meunier, Bernadette

A2 - Yager, Ronald R.

A2 - Zadeh, Lotfi A.

PB - Springer

ER -