ANSS '07 Proceedings of the 40th Annual Simulation Symposium
On the automation of computer network simulators
Proceedings of the 2nd International Conference on Simulation Tools and Techniques
A flexible and extensible architecture for experimental model validation
Proceedings of the 3rd International ICST Conference on Simulation Tools and Techniques
Template and Frame Based Experiment Workflows in Modeling and Simulation Software with WORMS
SERVICES '12 Proceedings of the 2012 IEEE Eighth World Congress on Services
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With the rising number and diversity of simulation experiment methods, the need for a tool supporting an easy exploitation of those methods emerges. We introduce GUISE, an experiment tool to support users in conducting experiments. We structure simulation experiments according to six tasks: specification, configuration of model parameters, simulation, data collection, analysis, and evaluation. This structure provides the required flexibility to seamlessly integrate various methods into the tool and combine them to pursue different goals (e.g., validation, optimization, etc.). To support experimenters in selecting and composing suitable methods, GUISE exploits machine learning techniques, which we illustrate at the example of steady-state estimation.