Bayesian Belief Nets (BBNs) have proven to be an extremely powerful technique for reasoning under uncertainty. We have used them in a range of real applications concerned with predicting properties of critical systems. In most of these applications we are interested in a single attribute of the system such as safety, reliability, or defect-density. Although such BBNs provide important support for decision making, in many circumstances we need to make decisions based on multiple criteria. For example, a BBN for predicting the safety of a critical system cannot be used to make a decision about whether or not the system should be deployed. This is because such a decision must be based on criteria other than just safety (cost, politics, and en...
ABSTRACT: The authors have recently completed a causal model for aviation safety under contract with...
The paper demonstrates the use of Bayesian networks in multicriteria decision analysis (MCDA) of env...
Bayesian decision analysis supports principled decision making in complex domains. This textbook tak...
In decision problems that rely on technical or scientific data, values are often not explicitly cons...
Bayesian belief nets (BBNs) provide an effective way of reasoning under uncertainty. They have a fir...
Abstract The formalism of Bayesian Belief Networks (BBNs) is being increasingly applied to probabili...
This book is an extension of the author’s first book and serves as a guide and manual on how to spec...
We live in an era where every human entity, from a simple citizen to the head of an entity as large ...
The objective of this paper is to present a new approach to reasoning under uncertainty, based on th...
The legal requirement in the UK for the duty holder of a chemical process plant to demonstrate that ...
International audienceLiquid petroleum gas (LPG) is one area where catastrophic release scenarios ha...
This paper is concerned with decision support system (DSS) development for aid in decision-making wi...
In: Integrated Intelligent Systems for Engineering Design (editors: Zha, X.F. and Howlett, R.J.)...
An information fusion system with local sensors sometimes requires the capability to represent the t...
An integrated model for risk in a real-time environment for the hydrocarbon industry based on the CA...
ABSTRACT: The authors have recently completed a causal model for aviation safety under contract with...
The paper demonstrates the use of Bayesian networks in multicriteria decision analysis (MCDA) of env...
Bayesian decision analysis supports principled decision making in complex domains. This textbook tak...
In decision problems that rely on technical or scientific data, values are often not explicitly cons...
Bayesian belief nets (BBNs) provide an effective way of reasoning under uncertainty. They have a fir...
Abstract The formalism of Bayesian Belief Networks (BBNs) is being increasingly applied to probabili...
This book is an extension of the author’s first book and serves as a guide and manual on how to spec...
We live in an era where every human entity, from a simple citizen to the head of an entity as large ...
The objective of this paper is to present a new approach to reasoning under uncertainty, based on th...
The legal requirement in the UK for the duty holder of a chemical process plant to demonstrate that ...
International audienceLiquid petroleum gas (LPG) is one area where catastrophic release scenarios ha...
This paper is concerned with decision support system (DSS) development for aid in decision-making wi...
In: Integrated Intelligent Systems for Engineering Design (editors: Zha, X.F. and Howlett, R.J.)...
An information fusion system with local sensors sometimes requires the capability to represent the t...
An integrated model for risk in a real-time environment for the hydrocarbon industry based on the CA...
ABSTRACT: The authors have recently completed a causal model for aviation safety under contract with...
The paper demonstrates the use of Bayesian networks in multicriteria decision analysis (MCDA) of env...
Bayesian decision analysis supports principled decision making in complex domains. This textbook tak...