This article presents the results of a multi-objective collaboration between the Learning Agents Laboratory of George Mason University, on the one side, and the Center for Strategic Leadership and the Department of Military Strategy, Planning, and Operations of the U.S. Army War College, on the other side. A distinguishing feature of this collaboration is the synergistic integration of AI research with military strategy research and the practical use of agents in education, as detailed in the following.
The AI research objective is the development of the DISCIPLE approach for building instructable knowledge-based systems or agents (Tecuci 1998, 1988). The DISCIPLE approach advocates the creation of a powerful learning agent shell that can be taught by a person to solve problems in a way similar to how that person would teach a student or an assistant.
We think that the DISCIPLE approach contributes directly to a new age in the software systems development process, as illustrated in figure 1. In the mainframe computers age, the software systems were both built and used by computer science experts. In the current age of personal computers, these systems are still being built by computer science experts, but many of them (such as text processors, electronic-mail programs, or internet browsers) are now used by persons that have no formal computer education. Continuing this trend, we think that the next age will be that of the personal agents, where typical computer users will be able to both develop and use special types of software agents (Tecuci, Boicu, and Marcu 2000). The DISCIPLE approach attempts to change the way intelligent agents are built, from "being programmed" by a knowledge engineer to "being taught" by a user who does not have prior knowledge engineering or computer science experience. This approach would allow a typical computer user, who is not a trained knowledge engineer, to build by himself/herself an intelligent assistant as easily as he/she now uses a word processor to write a paper.
[FIGURE 1 OMITTED]
Over the years, we have developed a series of increasingly advanced learning agent shells forming the DISCIPLE family. The most recent family member, DISCIPLE-RKF, represents a significant advancement over its most recent predecessors: DISCIPLE-WA (Tecuci et al. 1999) and DISCIPLE-COA (Tecuci et al. 2001). All three systems were developed as part of the High Performance Knowledge Bases Program and the Rapid Knowledge Formation Program, supported by the Defense Advanced Research Projects Agency (DARPA) and the Air Force Office of Scientific Research (AFOSR). (1) Both programs emphasized the use of innovative challenge problems to focus and evaluate the research and development efforts. The challenge problem for the DISCIPLE-RKF system is the strategic center of gravity analysis, which brings us to the second objective of this effort, the military strategy research objective of clarifying and formalizing the center of gravity analysis process by using the general task-reduction paradigm of problem solving. The concept of the center of gravity of an entity (state, alliance, coalition, or group) was introduced in the nineteenth century by Karl von Clausewitz (1976) as the foundation of capability, "the hub of all power and movement, on which everything depends, ... the point against which all the energies should be directed" (595-596).
Correctly identifying the centers of gravity of the opposing forces is of highest importance in any conflict. Therefore, in the education of strategic leaders at all the United States senior military service colleges, there is a great emphasis on the center of gravity analysis (Strange 1996). Hence, we have the third objective of this research, the educational objective of enhancing the educational process of senior military officers through the use of intelligent agent technology. Using the DISCIPLE approach, we have developed intelligent agents for strategic center of gravity analysis that are used in several courses at the U. …