260 research outputs found
Intuitions and the modelling of defeasible reasoning: some case studies
The purpose of this paper is to address some criticisms recently raised by
John Horty in two articles against the validity of two commonly accepted
defeasible reasoning patterns, viz. reinstatement and floating conclusions. I
shall argue that Horty's counterexamples, although they significantly raise our
understanding of these reasoning patterns, do not show their invalidity. Some
of them reflect patterns which, if made explicit in the formalisation, avoid
the unwanted inference without having to give up the criticised inference
principles. Other examples seem to involve hidden assumptions about the
specific problem which, if made explicit, are nothing but extra information
that defeat the defeasible inference. These considerations will be put in a
wider perspective by reflecting on the nature of defeasible reasoning
principles as principles of justified acceptance rather than `real' logical
inference.Comment: Proceedings of the 9th International Workshop on Non-Monotonic
Reasoning (NMR'2002), Toulouse, France, April 19-21, 200
AI & Law, logic and argument schemes
This paper reviews the history of AI & Law research from the perspective of argument schemes. It starts with the observation that logic, although very well applicable to legal reasoning when there is uncertainty, vagueness and disagreement, is too abstract to give a fully satisfactory classification of legal argument types. It therefore needs to be supplemented with an argument-scheme approach, which classifies arguments not according to their logical form but according to their content, in particular, according to the roles that the various elements of an argument can play. This approach is then applied to legal reasoning, to identify some of the main legal argument schemes. It is also argued that much AI & Law research in fact employs the argument-scheme approach, although it usually is not presented as such. Finally, it is argued that the argument-scheme approach and the way it has been employed in AI & Law respects some of the main lessons to be learnt from Toulmin's The Uses of Argument
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