Applications of a Theory of Automated Adversarial Planning to Command and Control

Abstract
One of the potentially most valuable research areas within artificial intelligence (Al), from the standpoint of military applications, involves the development of automatic planning systems. Al planners not only have the potential of autonomously solving various low-level planning problems such as those found in robotics applications, but can form the basis of expert consultation systems for higher level military planning problems including those involving command and control. An overview of a theory of automated adversarial planning is presented, which has been derived from the enhancement and expansion of AI techniques from the areas of automated planning and knowledge-based computer game playing. The adversarial planning paradigm has been successfully implemented in ARES (adversarial reasoning system), a computer program which can plan sequences of robot actions and compete in game environments, where various kinds of adversity (including intelligent adversarial counterplanners) exist.

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