[HTML][HTML] Theory of mind and preference learning at the interface of cognitive science, neuroscience, and AI: A review
Theory of Mind (ToM)-the ability of the human mind to attribute mental states to others-is a
key component of human cognition. In order to understand other people's mental states or …
key component of human cognition. In order to understand other people's mental states or …
[图书][B] Algorithms for decision making
A broad introduction to algorithms for decision making under uncertainty, introducing the
underlying mathematical problem formulations and the algorithms for solving them …
underlying mathematical problem formulations and the algorithms for solving them …
A novel quantum model of mass function for uncertain information fusion
X Deng, S Xue, W Jiang - Information Fusion, 2023 - Elsevier
Understanding the uncertainty involved in a mass function is a central issue in Dempster–
Shafer evidence theory for uncertain information fusion. Recent advances suggest to …
Shafer evidence theory for uncertain information fusion. Recent advances suggest to …
Random permutation set reasoning
In artificial intelligence, it is crucial for pattern recognition systems to process data with
uncertain information, necessitating uncertainty reasoning approaches such as evidence …
uncertain information, necessitating uncertainty reasoning approaches such as evidence …
Entropy of random permutation set
Recently, a new kind of set, named Random Permutation Set (RPS), has been presented.
RPS takes the permutation of a certain set into consideration, which can be regarded as an …
RPS takes the permutation of a certain set into consideration, which can be regarded as an …
Uncertainty measures: A critical survey
F Cuzzolin - Information Fusion, 2024 - Elsevier
Classical probability is not the only mathematical theory of uncertainty, or the most general.
Many authors have argued that probability theory is ill-equipped to model the 'epistemic' …
Many authors have argued that probability theory is ill-equipped to model the 'epistemic' …
A framework for the fusion of non-exclusive and incomplete information on the basis of D number theory
X Deng, W Jiang - Applied Intelligence, 2023 - Springer
Uncertainty is of great concern in information fusion and artificial intelligence. Dempster-
Shafer theory is a popular tool to deal with uncertainty, but it cannot effectively represent and …
Shafer theory is a popular tool to deal with uncertainty, but it cannot effectively represent and …
Is the volume of a credal set a good measure for epistemic uncertainty?
Adequate uncertainty representation and quantification have become imperative in various
scientific disciplines, especially in machine learning and artificial intelligence. As an …
scientific disciplines, especially in machine learning and artificial intelligence. As an …
Higher order information volume of mass function
For a certain moment, the information volume of probability space can be accurately
expressed by Shannon entropy. But in real life, the distribution of events usually change …
expressed by Shannon entropy. But in real life, the distribution of events usually change …
[HTML][HTML] A clustering based method to complete frame of discernment
Y Wenran, LI Xinde, D Yong - Chinese Journal of Aeronautics, 2023 - Elsevier
When the existing information does not contain all categories, the Generalized Evidence
Theory (GET) can deal with information fusion. However, the question of how to determine …
Theory (GET) can deal with information fusion. However, the question of how to determine …