Epistemology is concerned with the fundamental laws of thought, belief, or judgment. It may
inquire the fundamental relations among the objects or contents of thought and belief, ie …

Degrees of belief are familiar to all of us. Our confidence in the truth of some propositions is
higher than our confidence in the truth of other propositions. We are pretty confident that our …

Different qualitative models have been proposed for decision under uncertainty in Artificial
Intelligence, but they generally fail to satisfy the principle of strict Pareto dominance or …

The aim of this work is to provide a unified framework for ordinal representations of
uncertainty lying at the crosswords between possibility and probability theories. Such …

We propose a framework and algorithms for reinforcement learning in sequential decision
problems under uncertainty in which the rewards are qualitative, and/or are temporarily …

Epistemology is concerned with the fundamental laws of thought, belief, or judgment. It may
inquire the fundamental relations among the objects or contents of thought and belief, ie …

Possibilistic networks are important tools for modelling and reasoning, especially in the
presence of imprecise and/or uncertain information. These graphical models have been …

Understanding why a classifier makes a certain prediction is crucial in high-stakes
applications. It is also one of the central problems studied in the field of Explainable AI. To …

Les réseaux possibilistes représentent des outils importants de modélisation et de
raisonnement, en particulier, en présence d'informations imprécises et/ou incertaines. Ces …

Spohnian ranking functions are a qualitative abstraction of probability functions, and they
have been applied to knowledge representation and reasoning that involve uncertainty …