Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Assignment of available products to orders with the MCDM software Oreste
Applied Mathematics and Computation - Special issue on multicriterion decision making with engineering applications
Artificial Intelligence - Special issue on nonmonotonic reasoning
Using Ranked Nodes to Model Qualitative Judgments in Bayesian Networks
IEEE Transactions on Knowledge and Data Engineering
An approach to hybrid probabilistic models
International Journal of Approximate Reasoning
Information Sciences: an International Journal
Modeling and Reasoning with Bayesian Networks
Modeling and Reasoning with Bayesian Networks
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
Journal of Artificial Intelligence Research
Expert Systems with Applications: An International Journal
On the revision of probabilistic beliefs using uncertain evidence
Artificial Intelligence
Agent-encapsulated Bayesian networks and the rumor problem
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Expert Systems with Applications: An International Journal
Algorithms for fuzzy multi expert multi criteria decision making (ME-MCDM)
Knowledge-Based Systems
Expected value method for intuitionistic trapezoidal fuzzy multicriteria decision-making problems
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Remote decision support for wheeled mobility and seating devices
Expert Systems with Applications: An International Journal
A probabilistic decision-making approach for the sustainable assessment of infrastructures
Expert Systems with Applications: An International Journal
Influence diagrams with multiple objectives and tradeoff analysis
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Hi-index | 12.05 |
This paper discusses recurrent multi-criteria, multi-attribute decision problems. Because of the possibility of decision-maker ignorance or low decision-maker involvement the decision problem structuring is done once for all by a group of experts and does not involve the implication of the decision makers. We propose an original model based on Bayesian networks, which provides a decision process that helps the decision-maker to select an appropriate alternative among a set of alternatives, taking into account multiple criteria that are often conflicting. Our model makes it possible to represent in the same model the decision case (i.e., the decision-maker characteristics, contextual characteristics, their needs and preferences), the set of alternatives with the different attributes, and the choice criteria. The model allows us to compute the value of three essential elements: the importance of each criterion, which is based on the decision-case characteristics; each criterion's evaluation index in terms of the alternative; and each criterion's satisfaction index. The recurrent problem of choosing a manual wheelchair (MWC) illustrates the construction and use of our model.