Reasoning paradigms in legal decision support systems

Zeleznikow, John & Hunter, Dan (1995) Reasoning paradigms in legal decision support systems. Artificial Intelligence Review, 9(6), pp. 361-385.

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Abstract

In this paper we discuss the strengths and weaknesses of a range of artificial intelligence approaches used in legal domains. Symbolic reasoning systems which rely on deductive, inductive and analogical reasoning are described and reviewed. The role of statistical reasoning in law is examined, and the use of neural networks analysed. There is discussion of architectures for, and examples of, systems which combine a number of these reasoning strategies. We conclude that to build intelligent legal decision support systems requires a range of reasoning strategies.

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ID Code: 71068
Item Type: Journal Article
Refereed: Yes
DOI: 10.1007/BF00849064
ISSN: 1573-7462
Divisions: Current > QUT Faculties and Divisions > Faculty of Law
Copyright Owner: Copyright 1995 Springer Netherlands
Deposited On: 06 May 2014 03:54
Last Modified: 21 Jun 2017 05:01

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