Decision Aids for Adversarial Planning in Military Operations:
  Algorithms, Tools, and Turing-test-like Experimental Validation
  Use of intelligent decision aids can help alleviate the challenges of
planning complex operations. We describe integrated algorithms, and a tool
capable of translating a high-level concept for a tactical military operation
into a fully detailed, actionable plan, producing automatically (or with human
guidance) plans with realistic degree of detail and of human-like quality.
Tight interleaving of several algorithms -- planning, adversary estimates,
scheduling, routing, attrition and consumption estimates -- comprise the
computational approach of this tool. Although originally developed for Army
large-unit operations, the technology is generic and also applies to a number
of other domains, particularly in critical situations requiring detailed
planning within a constrained period of time. In this paper, we focus
particularly on the engineering tradeoffs in the design of the tool. In an
experimental evaluation, reminiscent of the Turing test, the tool's performance
compared favorably with human planners.
