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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Futo, I. Varkonyi, J. |
| Copyright Year | 1993 |
| Description | Author affiliation: Applied Logic Laboratory, Hungary (Futo, I.) |
| Abstract | In the paper the utilisation of legal expert systems for simulation is presented. Law in a general form prescribes the frame of possible behaviour of players in the domain regulated by it. A law can be considered as a set of rules forming a knowledge base and problems arising in the domain of its application should be answered based on it. In the last six years we developed a method to transform rules of law as it is published in statute--books into working expert systems. On the other hand simulation is the use of models to predict behaviour of existing or planned real system. If we consider the law as a model of the reality it is regulating, the corresponding expert system could be considered as the implemented version of this model on computers. Now by the use of these expert systems we can perform simulation. This simulation means the examination of the possible behaviour of the players which in some cases can be quantified by the use of statistical data. The method presented is particularly useful when one is framing new laws and wants to see the possible effects of the different proposed versions. Our method is mainly applicable for tax law, social security law, Finances Act or similar laws. |
| Starting Page | 1259 |
| Ending Page | 1263 |
| File Size | 392200 |
| Page Count | 5 |
| File Format | |
| ISBN | 078031381X |
| DOI | 10.1109/WSC.1993.718388 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1993-12-12 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Law Legal factors Expert systems Computational modeling Predictive models Economic forecasting Logic Laboratories Data security Uncertainty |
| Content Type | Text |
| Resource Type | Article |
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