JELIA 2012: Logics in Artificial Intelligence pp 411-423 | Cite as
Jumping to Conclusions
A Logico-Probabilistic Foundation for Defeasible Rule-Based Arguments
Conference paper
Abstract
A theory of defeasible arguments is proposed that combines logical and probabilistic properties. This logico-probabilistic argumentation theory builds on two foundational theories of nonmonotonic reasoning and uncertainty: the study of nonmonotonic consequence relations (and the associated minimal model semantics) and probability theory. A key result is that, in the theory, qualitatively defined argument validity can be derived from a quantitative interpretation. The theory provides a synthetic perspective of arguments ‘jumping to conclusions’, rules with exceptions, and probabilities.
Keywords
Structure Argument Quantitative Interpretation Valid Argument Inference Relation Nonmonotonic Reasoning
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