  This paper defines adversarial reasoning as computational approaches to
inferring and anticipating an enemy's perceptions, intents and actions. It
argues that adversarial reasoning transcends the boundaries of game theory and
must also leverage such disciplines as cognitive modeling, control theory, AI
planning and others. To illustrate the challenges of applying adversarial
reasoning to real-world problems, the paper explores the lessons learned in the
CADET - a battle planning system that focuses on brigade-level ground
operations and involves adversarial reasoning. From this example of current
capabilities, the paper proceeds to describe RAID - a DARPA program that aims
to build capabilities in adversarial reasoning, and how such capabilities would
address practical requirements in Defense and other application areas.
