Full-text resources of CEJSH and other databases are now available in the new Library of Science.
Visit https://bibliotekanauki.pl

PL EN


2013 | 2(7) | 52-62

Article title

Sztuczne sieci neuronalne w modelowaniu rozumowań prawniczych. O problemach wynikających ze specyfiki prawa

Content

Title variants

EN
Application of artificial neural networks for modeling legal reasoning. On legal reasoning specific problems

Languages of publication

PL

Abstracts

PL
The purpose of this paper is to describe the application of artificial neural networks in modeling legal reasoning. In particular, the paper will be focused on specific problems which may occur only on the ground of legal reasoning and are difficult from the artificial intelligence perspective. The focal point of the paper is not to provide technical details of analyzed systems but to point out parts of legal conceptual framework which are inconsistent with classical techniques of designing of expert system. Paper consists description of a few legal expert systems based on artificial neural networks. Each of them is the basis for presentation of particular feature of legal reasoning which are considered difficult from the AI point of view e.g. vague concepts, open-texture, analogy.
EN
The purpose of this paper is to describe the application of artificial neural networks in modeling legal reasoning. In particular, the paper will be focused on specific problems which may occur only on the ground of legal reasoning and are difficult from the artificial intelligence perspective. The focal point of the paper is not to provide technical details of analyzed systems but to point out parts of legal conceptual framework which are inconsistent with classical techniques of designing of expert system. Paper consists description of a few legal expert systems based on artificial neural networks. Each of them is the basis for presentation of particular feature of legal reasoning which are considered difficult from the AI point of view e.g. vague concepts, open-texture, analogy.

Year

Volume

Pages

52-62

Physical description

Dates

published
2013

Contributors

References

Notes

PL

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.desklight-c017f21a-d451-46f0-b6dd-02c739cf0004
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.