Graphical readings of possibilistic logic bases
Salem Benferhat, Didier Dubois, Souhila Kaci, Henri Prade

TL;DR
This paper explores graphical representations of possibilistic logic bases using product-based causal graphs, offering structural and preference-based interpretations to better understand uncertainty and goal priorities.
Contribution
It introduces a novel product-based graphical framework for possibilistic logic bases and links them to preference structures, enhancing interpretability.
Findings
Provides a structural reading of possibilistic bases via product-based graphs.
Introduces a preference-based interpretation of possibilistic bases.
Connects possibilistic logic with goal prioritization through preferences.
Abstract
Possibility theory offers either a qualitive, or a numerical framework for representing uncertainty, in terms of dual measures of possibility and necessity. This leads to the existence of two kinds of possibilistic causal graphs where the conditioning is either based on the minimum, or the product operator. Benferhat et al. (1999) have investigated the connections between min-based graphs and possibilistic logic bases (made of classical formulas weighted in terms of certainty). This paper deals with a more difficult issue : the product-based graphical representations of possibilistic bases, which provides an easy structural reading of possibilistic bases. Moreover, this paper also provides another reading of possibilistic bases in terms of comparative preferences of the form "in the context p, q is preferred to not q". This enables us to explicit preferences underlying a set of goals…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsLogic, Reasoning, and Knowledge · Advanced Algebra and Logic · Bayesian Modeling and Causal Inference
