Successful completion of a complex agent training experiment at the US Army War College

    In the Spring 2002 session of the “Military Applications of Artificial Intelligence” course, we have conducted a complex agent training experiment.  Seven teams comprising 15 senior military officers used personal copies of the Disciple-RKF/COG learning agent.  Each team has taught its agent not only to identify center of gravity candidates (as was the case in the previous, Spring 2001, experiment), but also to test these candidates and eliminate those which are not the center of gravity.  Testing of candidates is a much more complex activity than identifying them, therefore this was a very challenging experiment aimed at clarifying the main strengths and weaknesses of the Disciple approach.  Each team trained its agent using a single scenario, by explaining to the agent how to identify and test the strategic COG candidates for the opposing forces in that scenario.  At the end of the training phase, the developed agents were tested on new scenarios.  For instance, the following figure shows how each of the developed agents analyzed the Grenada scenario.  A yellow dot on a row corresponding to a COG candidate indicates that the candidate was identified by the agent from the column of that dot. A red dot indicates that after further analysis the candidate was eliminated. A green dot indicates that the candidate passed all the testes and was not eliminated, indicating that it could be the actual COG.  In one example, the agent trained with the Malaya scenario has identified “will of the people of Grenada” as a strategic center of gravity candidate for the Grenadan coalition and then, after further testing, it has eliminated it.

Application of partially trained agents on the Grenada scenario.

    Notice that although each agent was trained with only one scenario (indicated at the top of each column), their performance is reasonably good.  This demonstrates the power of the Disciple learning methods, which allow the agent to learn useful reasoning rules from only one or two examples.

    At the end of the experiment 9 out of the 15 experts agreed, 2 strongly agreed and 4 were neutral with respect to the following statement: "I think that a subject matter expert can use Disciple to build an agent, with limited assistance from a knowledge engineer." This is a very important result which confirms the one obtained in the previous year, in spite of the fact that the teaching required this time was significantly more complex. 

The following are some general assessments made by the students (military experts):