Cristina Cornelio, Judy Goldsmith, et al.
JAIR
In this paper, we develop a qualitative theory of influence diagrams that can be used to model and solve sequential decision making tasks when only qualitative (or imprecise) information is available. Our approach is based on an orderof-magnitude approximation of both probabilities and utilities and allows for specifying partially ordered preferences via sets of utility values. We also propose a dedicated variable elimination algorithm that can be applied for solving order-of-magnitude influence diagrams.
Cristina Cornelio, Judy Goldsmith, et al.
JAIR
Pavel Klavík, A. Cristiano I. Malossi, et al.
Philos. Trans. R. Soc. A
Erik Altman, Jovan Blanusa, et al.
NeurIPS 2023
Conrad Albrecht, Jannik Schneider, et al.
CVPR 2025