Validating Computational Human Behavior Models: Consistency and Accuracy Issues
Abstract
As leaders of the Department of Defense (DoD) rely more on modeling and simulation (M&S) to provide information on which they base strategies and tactical decisions, the credibility of simulation becomes more important. This credibility is initially gained through the verification, validation, and accreditation process DoD models are required to undergo prior to their use in simulations. The process of validating behavioral models is not well defined, nor is the process extendable to meet requirements for validating the varied and complex behavioral models. Through a series of empirical studies, this research identifies subject matter expert (SME) biases and their effects on consistency and accuracy of results. This research concludes that an SME's bias has a statistically significant effect on subjective assessment of human performance of urban combat skills. To this end, the research demonstrates how the effects of the natural biases of SMEs can be mitigated based on the scale used to assess human behavior representation (HBR) models, providing a more consistent and accurate means of validating HBR models. In doing so, it assists the DoD M&S Community by providing enhancements to face validation procedures for assessing HBR model implementations for future use in DoD legacy and developmental combat models. (39 tables, 77 figures, 125 refs.)
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2004
- Accession Number
- ADA425090
Entities
People
- Simon R. Goerger
Organizations
- Naval Postgraduate School