Artificial Intelligence Technique to Generate Self-Optimizing Experimental Designs.

摘要

The paper describes a completed and independent module of a large-scale system, the Quasi-Optimizer (QO). the QO system has three major objectives: (1) to observe and measure adversaries' behavior in a competitive environment, to infer their strategies and to construct a computer model, a descriptive theory, of each; (2) to identify strategy components, evaluate their effectiveness and to select the most satisfactory ones from a set of computed descriptive theories; and (3) to combine these components in a quasi-optimum strategy that represents a normative theory in the statistical sense.