Simulation Study Shows Real Intel Eliminates Guessing Risk, Not Just Adds Advantage

A developer running a tactical battle simulation tested four command doctrines across 80 seeded runs each on the same blind mountain-pass scenario to measure how much accurate enemy positioning matters. The results showed that a cautious fixed-schedule doctrine won zero of eighty engagements, while a well-tuned guessing approach already outperformed it, and full real-time information achieved a perfect 80/80 win rate. Two new systems were added since a previous experiment: a fog-of-war layer that filters each faction's perception without altering the core engine, and a conditional-order system that triggers actions based on perceived battlefield state rather than fixed timing. A single conditional order tied the performance of a manually tuned doctrine at roughly 17/80 wins, requiring no calibration, but fell far short of full scripted decision-making because it locks a commander into one course of action after firing. The key takeaway recorded in the project's documentation is that information does not make a force more aggressive — it removes the risk of acting on a wrong assumption.