[HTML][HTML] Theory of mind and preference learning at the interface of cognitive science, neuroscience, and AI: A review

C Langley, BI Cirstea, F Cuzzolin… - Frontiers in artificial …, 2022 - frontiersin.org
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 …

[图书][B] Algorithms for decision making

MJ Kochenderfer, TA Wheeler, KH Wray - 2022 - books.google.com
A broad introduction to algorithms for decision making under uncertainty, introducing the
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 …

Random permutation set reasoning

J Deng, Y Deng, JB Yang - IEEE Transactions on Pattern …, 2024 - ieeexplore.ieee.org
In artificial intelligence, it is crucial for pattern recognition systems to process data with
uncertain information, necessitating uncertainty reasoning approaches such as evidence …

Entropy of random permutation set

L Chen, Y Deng - Communications in Statistics-Theory and …, 2024 - Taylor & Francis
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 …

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' …

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 …

Is the volume of a credal set a good measure for epistemic uncertainty?

Y Sale, M Caprio, E Höllermeier - Uncertainty in Artificial …, 2023 - proceedings.mlr.press
Adequate uncertainty representation and quantification have become imperative in various
scientific disciplines, especially in machine learning and artificial intelligence. As an …

Higher order information volume of mass function

Q Zhou, Y Deng - Information Sciences, 2022 - Elsevier
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 …

[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 …