A dialectical model of assessing conflicting arguments in legal reasoning

Artificial Intelligence and Law 4 (3-4):331-368 (1996)
Inspired by legal reasoning, this paper presents a formal framework for assessing conflicting arguments. Its use is illustrated with applications to realistic legal examples, and the potential for implementation is discussed. The framework has the form of a logical system for defeasible argumentation. Its language, which is of a logic-programming-like nature, has both weak and explicit negation, and conflicts between arguments are decided with the help of priorities on the rules. An important feature of the system is that these priorities are not fixed, but are themselves defeasibly derived as conclusions within the system. Thus debates on the choice between conflicting arguments can also be modelled.The proof theory of the system is stated in dialectical style, where a proof takes the form of a dialogue between a proponent and an opponent of an argument. An argument is shown to be justified if the proponent can make the opponent run out of moves in whatever way the opponent attacks. Despite this dialectical form, the system reflects a declarative, or relational approach to modelling legal argument. A basic assumption of this paper is that this approach complements two other lines of research in AI and Law, investigations of precedent-based reasoning and the development of procedural, or dialectical models of legal argument.
Keywords argumentation  defeasibility  dialectics  rule conflicts  logic programming
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DOI 10.1007/BF00118496
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References found in this work BETA
R. P. Loui & Jeff Norman (1995). Rationales and Argument Moves. Artificial Intelligence and Law 3 (3):159-189.

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