Goal driven simulation intelligent back ends: a state of the art review

Goal driven simulation (GDS) seeks to automate many of the output analysis and experimental design tasks of a simulation study. Theoretically, its use allows the reallocation of the simulation expert to other tasks. ODS capabilities include determining parameters to change, suggesting a rate of chan...

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Bibliographic Details
Main Authors: Molina, Louis A., Gandarillas, Carlos, Centeno, Martha A.
Format: Conference Proceeding
Language:English
Subjects:
Analytical models
Computational modeling
Computer simulation
Context modeling
Design engineering
Educational institutions
Flexible manufacturing systems
Information systems
Information systems > Information systems applications
Information systems > Information systems applications > Decision support systems
Information systems > Information systems applications > Decision support systems > Expert systems
Object oriented modeling
Packaging
Systems engineering and theory
Online Access:Request full text
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Description
Summary:Goal driven simulation (GDS) seeks to automate many of the output analysis and experimental design tasks of a simulation study. Theoretically, its use allows the reallocation of the simulation expert to other tasks. ODS capabilities include determining parameters to change, suggesting a rate of change, and testing these changes against a pre-established set of goals. Realizing GDS, however, requires the integration of techniques such as object oriented design, knowledge based systems, and neural nets. Before achieving this integration, there are still several issues to resolve including the type of interaction these techniques would have among themselves. This paper explores several of the issues concerning the realization of goal driven simulation systems, their impact on the simulation modeling methodology, how GDS works, and the need for its development.
DOI:10.1145/256562.256798