An explication of uncertain evidence in Bayesian networks: Likelihood evidence and probabilistic evidence: Uncertain evidence in Bayesian networks
This paper proposes a systematized presentation and a terminology for observations in a
Bayesian network. It focuses on the three main concepts of uncertain evidence, namely …
Bayesian network. It focuses on the three main concepts of uncertain evidence, namely …
Expert system for medicine diagnosis using software agents
O Arsene, I Dumitrache, I Mihu - Expert Systems with Applications, 2015 - Elsevier
In order to simplify the information exchange within the medical diagnosis process, a
collaborative software agents framework is presented. The human body systems (eg …
collaborative software agents framework is presented. The human body systems (eg …
Paid: A probabilistic agent-based intrusion detection system
In this paper we describe architecture and implementation of a Probabilistic Agent-Based
Intrusion Detection (PAID) system. The PAID system has a cooperative agent architecture …
Intrusion Detection (PAID) system. The PAID system has a cooperative agent architecture …
[HTML][HTML] How to model mutually exclusive events based on independent causal pathways in Bayesian network models
We show that existing Bayesian network (BN) modelling techniques cannot capture the
correct intuitive reasoning in the important case when a set of mutually exclusive events …
correct intuitive reasoning in the important case when a set of mutually exclusive events …
A knowledge integration framework for complex network management
Purpose–Large supply and computer networks contain heterogeneous information and
correlation among their components, and are distributed across a large geographical region …
correlation among their components, and are distributed across a large geographical region …
An approach to hybrid probabilistic models
E Di Tomaso, JF Baldwin - International Journal of Approximate Reasoning, 2008 - Elsevier
This paper is concerned with a development of a theory on probabilistic models, and in
particular Bayesian networks, when handling continuous variables. While it is possible to …
particular Bayesian networks, when handling continuous variables. While it is possible to …
[PDF][PDF] Agent-encapsulated Bayesian networks and the rumor problem.
S Langevin, M Valtorta, M Bloemeke - AAMAS, 2010 - researchgate.net
We present a multiagent organization for data interpretation and fusion in which each agent
uses an encapsulated Bayesian network for knowledge representation, and agents …
uses an encapsulated Bayesian network for knowledge representation, and agents …
Performance evaluation of algorithms for soft evidential update in Bayesian networks: First results
S Langevin, M Valtorta - … Conference, SUM 2008, Naples, Italy, October 1 …, 2008 - Springer
In this paper we analyze the performance of three algorithms for soft evidential update, in
which a probability distribution represented by a Bayesian network is modified to a new …
which a probability distribution represented by a Bayesian network is modified to a new …
Developing taxonomy and model for security centric supply chain management
Security management of modern supply systems raise challenges to various aspects of
Supply Chain Management (SCM) researches, demanding an integrated and holistic …
Supply Chain Management (SCM) researches, demanding an integrated and holistic …
On the combination of logical and probabilistic models for information analysis
Formal logical tools are able to provide some amount of reasoning support for information
analysis, but are unable to represent uncertainty. Bayesian network tools represent …
analysis, but are unable to represent uncertainty. Bayesian network tools represent …