A Logic of Uncertain Interpretation
This work addresses foundational challenges in logic and AI for reasoning under uncertainty, presenting incremental advancements in formal semantics and belief representation.
The authors introduced a logical framework for reasoning about uncertain interpretations, developing a new semantics for implication that captures meaning entailment and a conservative notion of evidentially supported belief modeled as a Dempster-Shafer belief function.
We introduce a logical framework for reasoning about "uncertain interpretations" and investigate two key applications: a new semantics for implication capturing a kind of "meaning entailment", and a conservative notion of "evidentially supported" belief that takes the form of a Dempster-Shafer belief function.