The domain in which we explored the design of our pedagogical agent is virtual world simulation for the training of military tank crews. These simulations are based on DIS technology whereby independent simulators are tied together over a network, communicating low level simulation events to create a large-scale simulation environment. The various entities interacting in this simulation environment can include teams of students in tank simulators as well as synthetic forces (semi-autonomous forces) generated by software such as the ModSAF (Modular Semi-Autonomous Forces) program [2].
In a typical platoon exercise, there are four tank simulators, each manned by four students, and approximately fifty synthetic forces. Additionally, a team of Army instructors will manage the exercise, performing the roles of superior officer (e.g., sending out changes in orders), teacher (e.g., providing guidance after the exercise during a review session) and adversary (e.g, dynamically creating and tasking opposing forces).
An exercise for a tank platoon might involve traveling in wedge formation to a location in order to occupy a position which blocks the opposing force. While in a wedge formation, there are guidelines as to how the individual tanks follow each other, keep each other in sight, etc. As the platoon travels to the position along the virtual terrain, it may encounter friendly or opposing forces to which it has to respond appropriately. These forces can be either synthetic or human agents and encounters with them can rapidly unfold in unpredictable ways. Likewise, the platoon may encounter terrain features that can slow down and/or damage its vehicles. Thus, the multi-agent dynamic qualities of the simulation can rapidly impact what needs to be done to satisfy the broadly scripted exercise, as well as whether it can be satisfied.
During the exercise, the instructors manage the simulation system in order to extract information and modify ongoing events, often to make the exercise more challenging. After the exercise, instructors will review key events for the students on 3-D displays.
Based on our observations of these exercises, instructors do not micromanage or even micro-evaluate the students. For instance, they don't analyze student behavior on an action-by-action basis unless the effect of a student's actions is something entirely anomalous in the current situation. An example of the latter would be if a tank comes to a halt while the platoon is supposed to be in a traveling wedge, thus disrupting the wedge. Finally, there are also individual differences in how instructors evaluate specific skills in the training context.
These characteristics are consistent with the nature of the domain and the skills that need to be acquired. Because of the dynamic, multi-agent domain, there is no guaranteed plan for achieving the goals set out for the students. Without such a plan, or other agreed upon objective basis, micro-evaluation at the level of each and every individual action is problematic. Furthermore, understanding the rationale for every action may require modeling the domain from the perspective of every student, e.g., down to the level of every rock which must be circumnavigated to avoid tread damage. Also, because of the dynamic domain, it is necessary to foster the development of initiative in the teams consistent with situation-appropriate goals and behaviors.
Although instructors do an excellent job of managing training exercises, the tools that they have at their disposal are severely lacking. Instructors are often forced to write notes to themselves on paper as the exercise proceeds, and must rely on subjective impressions. Also, as an exercise unfolds over time, relevant information concerning transient events or trends may be missed.
To see the obstacles that instructors currently face, consider Figure 1 which presents a 3D virtual view that an instructor might have of a platoon in a training exercise. One can see that the tanks are in a particular formation (it is a wedge formation). Things that are hard to tell from this picture are:
The information necessary to answer these questions is present in the simulation, if one looks for it in the right place and the right time. The goal of our pedagogical agent is to extract the information from the simulation automatically and to analyze it from the perspective of the instructor, permitting the instructor to focus on deciding where to provide instructional or adversarial feedback.
