Simulation and expert systems- A taxonomy and some examples

Author:

O'Keefe Robert1

Affiliation:

1. Board of Studies in Quantitative Social Science and Management Science Rutherford College The University of Kent at Canterbury Canterbury CT2 7NX United Kingdom

Abstract

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.

Publisher

SAGE Publications

Subject

Computer Graphics and Computer-Aided Design,Modeling and Simulation,Software

Reference35 articles.

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2. A-Razzax, M.; Hassan, T.; and Pettipher, R. "EXTRAN-77 (Expert Translator); a FORTRAN Based Software Package for Building Expert Systems." In Research and Developments in Expert Systems (Bramer, ed.). Cambndge University Press, Cambridge, U.K. (1984), 23-30.

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5. Cleary, J.; Goh, K.; and Unger, B. "Discete event simulation in Prolog." In Al, Graphics, and Simulation (G. Birtwistle, ed.), The Society for Computer Simulation, San Diego, Calif. (1985), 8-13.

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