Generating application-specific benchmark models for complex systems

  • Authors:
  • Jun Wang;Gregory Provan

  • Affiliations:
  • Department of Computer Science, University College Cork, Cork, Ireland;Department of Computer Science, University College Cork, Cork, Ireland

  • Venue:
  • AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
  • Year:
  • 2008

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Abstract

Automated generators for synthetic models and data can playa crucial role in designing new algorithms/model-frameworks, given the sparsity of benchmark models for empirical analysis and the cost of generating models by hand. We describe an automated generator for benchmark models that is based on using a compositional modeling framework and employs random-graph models for the system topology. We choose the system topology that best matches the topology of the real-world system using a domain-analysis algorithm. To show the range of models for which this approach is applicable, we demonstrate our model-generation process using two examples of model generation optimized for a specific domain: (1) model-based diagnosis for discrete Boolean circuits, and (2) E.coli TRN networks for simulating gene expression.