Modern military decision-making emphasizes the efficient conversion of information to action under uncertainty. Canonical frameworks such as Boyd’s Observe–Orient–Decide–Act (OODA) loop and Endsley’s model of Situational Awareness (SA) describe this process. To supplement these models, a measure called the HIT score is proposed, which functions as a proxy for both OODA and SA. The HIT score is a quantitative, nonintrusive, post hoc metric for information-processing efficiency. It is domain-agnostic and measures how effectively a system compresses environmental uncertainty into context-appropriate action within time constraints or other domain-specific costs. HIT depends on three observable or inferable components: H (Shannon entropy of the environment), I (mutual information between context and response), and T (decision time or cost). Formalisms for computing HIT are presented for single agents and networked settings. Empirical examples, including an iterated prisoner’s dilemma simulation and command and control (C2)-like scenarios, illustrate that HIT distinguishes adaptive strategies from those exhibiting mere random variability. Moreover, the metric is expanded by Petri Net-based approaches that are computationally tractable and practically applicable in both simulations and real-world scenarios. The HIT score provides a minimal quantitative bridge between information theory and operational decision-making in information-rich environments.
A Artturi Juvonen (Mon,) studied this question.