Simulation Validation for Societal Systems
Abstract
Simulation models are growing in size and complexity. As the size and complexity of the model increases so does the time and resources needed to validate the model. Multi-agent network models pose an even greater challenge for validation as they can be validated at the individual actor, the network, and/or the population level. There are however, substantial obstacles to validation. The nature of modeling means that there are implicit model assumptions, a complex model space and interactions, emergent behaviors, and uncodified and inoperable simulation and validation knowledge. The nature of the data, particularly in the realm of complex socio-technical systems poses still further obstacles to validation. These include sparse, inconsistent, old, erroneous, and mixed scale data. Given all these obstacles, the process of validating modern multi-agent network simulation models of complex socio-technical systems is such a herculean task that it often takes large groups of people years to accomplish. Automated and semi-automated tools are needed to support validation activities and so reduce the time and number of personnel needed. This thesis proposes such a tool. It advances the state of the art of simulation validation by using knowledge and ontological representation and inference. Advances are made at both conceptual and implementation or tool level.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2006
- Accession Number
- ADA457298
Entities
People
- Alex Yahja
Organizations
- Carnegie Mellon University