Algorithmic Tools for Adversarial Games

A key to successful command and control is to understand the enemy's intent, particularly in light of incomplete and perhaps inaccurate information regarding social and cultural norms. It is inappropriate to project our own goals and aspirations onto the enemy. Understanding the enemy's intent will become less a matter of understanding the thinking of higher command and more a matter of inferring the adversary's intent based on a priori beliefs regarding their objectives and observed data reflecting the actual decisions in real settings. A novel combination of two technologies, evolutionary computation and the Valuated State Spacer Approach used to quantifying purpose, holds the promise of a general procedure for inferring the enemy's purpose in combat settings ranging from the campaign-level to the level of the individual. The capability described in this proposal will generate an automatic method for optimizing models of the adversary's intent, structured in a hierarchic form. Natural Selection, Inc. will team with its academic partner UCSD on the Phase I effort. Success will allow for more effective course-of-action (COA) determination when viewing the sequence of actions and reactions because the adversary's mission will be better understood, allowing for more accurate predictions of his future behavior.