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Simulation and expert systems- A taxonomy and some examples
Robert O'Keefe
Board of Studies in Quantitative Social Science and Management Science Rutherford College The University of Kent at Canterbury Canterbury CT2 7NX United Kingdom
Simulation and expert systems are remarkably similar. Both employ various representations to model some aspect of an uncertain world, with the model being formed as a piece of com puter software. This is then employed to aid decision making. Ideas about combining simulation and expert systems are presented, and a taxonomy is developed. It is concluded that the most fruitful areas of cross-fertilization are advice-giving ex pert systems that assist the simulation scientist and simulation user, new simulation tools built from knowledge-based tools, and intelligent front ends for simulation packages. Advice-giving systems will increasingly be part of simulation environments, rather than stand alone. They will be aimed primarily at the in experienced simulationist. An example of a system developed in this vein, which advises on experimentation with transaction flow models, is presented. Regarding the use of knowledge-based tools, induction as an aid to the development of a discrete model is considered.
Key Words: artificial intelligence • expert systems • induction, simulation
SIMULATION, Vol. 46, No. 1,
10-16 (1986)
DOI: 10.1177/003754978604600102
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