Bayesian network (BN) modeling is a rapidly advancing field. Here we explore new methods
by which BN model development and application are being joined with other tools and …

Categorization is necessary for many decision making tasks. However, the categorization
process may interfere the decision making result and bring about the disjunction fallacy. To …

Abstract The Bayesian Network is a kind of probabilistic graphical models, having been
applied to various fields for inference and learning. A quantum-like Bayesian Network has …

Given the popular presupposition of human reasoning as the standard for learning and
decision making, there have been significant efforts and a growing trend in research to …

Group decision making (GDM) is widely used in a complex and uncertain real-world to help
multiple experts collectively evaluate and select appropriate alternatives. Consensus …

Multi-attribute decision making (MADM) is a classical model that widely used in various
fields. But most research about this topic often assume that the attributes are independent …

This article proposes a novel and comprehensive framework on how to describe the
probabilistic nature of decision-making process. We suggest extending the quantum-like …

Purpose Grey target decision-making serves as a pivotal analytical tool for addressing
dynamic multi-attribute group decision-making amidst uncertain information. However, the …

Multi-attribute group decision making (MAGDM) problem has become one of the most
remarkable topics recently. MAGDM is made up of multiple decision makers (DMs) who …

Due to the increasing complexity of decision tasks, the experiences, knowledge or opinions
from multiple decision makers (DMs) often need to be aggregated. Many multi-attribute …