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Modeling Human and Organizational Behavior: Application to Military Simulations
IF (situation x is true)
AND (event y is true within criteria z)
THEN (do action a with priority p)
The situational antecedent shown in the first line above ensures that only situationally relevant (e.g., for the right mission, in the right phase of the mission) rulesets are considered. The event trigger shown in the second line provides a "fuzzy" Boolean check by allowing for variable closeness in matching, through the parameter Z. Finally, the consequent in the third line specifies the action and also assigns it a priority, so that deconflicting or scheduling can occur when multiple actions are triggered in a given frame.
Operational plans in the NSS are represented either as open-loop plans, scripted by the user, or as reflexive, generated in the fashion just described by applying the appropriate tactical ruleset to the current tactical situation. Thus instead of "do action a with priority p," we might see "generate plan a with priority p." However, it is unclear whether actual plan generation is triggered by this production rule, or prestored contingency plans are retrieved from memory and issued by the command entity. An intermediate possibility, however, is suggested by the existence of another NSS module, the future enemy state predictor. Its function is to project the future battle status of the enemy some finite time into the future. Given this predicted future tactical situation, one could then apply the appropriate future tactical response. Since this situation would be in the future, it would become a response goal. Repetitive applications at multiple future time frames could then be used to generate multiple response goals, in effect producing a sequential plan for future actions and goals. Thus there would appear to be a mechanism (implemented or not) within the NSS for generating a tactical plan based on the anticipated evolution of the current tactical situation.
Automated Mission Planner
The University of Florida, in cooperation with the Institute for Simulation and Training at the University of Central Florida, is developing an automated mission planning (AMP) module for eventual incorporation into a command entity representing a company commander, as part of a ModSAF development effort within the DIS community (Lee and Fishwick, 1994; Karr, 1996). A four-stage planning process is outlined:
A terrain analyzer generates possible routes based on the current situation, the mission orders, and the terrain database.
A course-of-action generator uses "skeletal plans" (i.e., plan templates) to generate candidate courses of action identifying specific unit roles, routes, and tactical positions.
A course-of-action simulation runs through each candidate courseof