As the Army transforms itself into an organization of the future, emphasis on acquiring new military systems and training soldiers to use those new systems is a primary challenge. These transformation programs are also counting heavily on simulation-based acquisition and training as a means through which risk can be minimized and total ownership cost can be reduced. To truly evaluate aspects of human behavior that impacts system performance, we need to model how soldiers will perform the perceptual, cognitive, and physical tasks required. However, a human behavior modeling environment that includes both procedural and cognitive aspects of human behavior does not currently exist. In addition, the available cognitive modeling architectures are difficult to use and require expertise in programming, modeling, and cognitive science. This proposal outlines a work plan for developing a modeling environment that consists of task network discrete event simulation and a cognitive architecture in a unified and integrated package. The unified architecture is designed to be used by systems engineers, analysts, and human factors professionals without backgrounds in programming or cognitive science to evaluate proposed new systems and to provide realistic training experiences through development of semi automated forces that behave more realistically.
Benefits: Development of a unified modeling environment that includes both task network simulation capabilities and a cognitive architecture will take advantage of the strengths of each type of modeling while minimizing the shortcomings of each. The integrated environment will allow for a more complete representation of human behavior. Cognitive architectures force a fine grained approach to modeling human behavior. Task network models represent human behavior at a higher level of granularity. A benefit of a modeling environment that includes both is that models can be developed that can selectively represent behavior at the task level when it is appropriate yet allow for very fine grained models of cognition for portions of human behavior that are necessary. Both task network and cognitive models have been shown to be predictive of human behavior. Possibly the biggest benefit that we expect from this work will be that analysts, engineers, and system designers not trained in cognitive or computer science will be able to use the cognitive architecture to model human behavior.
Keywords: Task network modeling, cognitive architecture, human behavior, simulation, performance, system design
