ISSN:
1572-8382
Keywords:
analogy
;
fuzzy logic
;
learning
;
legal formalism
;
neural networks
;
vagueness
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
,
Law
Notes:
Abstract Computational approaches to the law have frequently been characterized as being formalistic implementations of the syllogistic model of legal cognition: using insufficient or contradictory data, making analogies, learning through examples and experiences, applying vague and imprecise standards. We argue that, on the contrary, studies on neural networks and fuzzy reasoning show how AI & law research can go beyond syllogism, and, in doing that, can provide substantial contributions to the law.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1008371600675
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