Reasoning paradigms in legal decision support systems


Autoria(s): Zeleznikow, John; Hunter, Dan
Data(s)

1995

Resumo

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.

Identificador

http://eprints.qut.edu.au/71068/

Publicador

Springer Netherlands

Relação

DOI:10.1007/BF00849064

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

Direitos

Copyright 1995 Springer Netherlands

Fonte

Faculty of Law; School of Law

Tipo

Journal Article