Military operations

Each unit is an agent with a platform record (speed, endurance, signatures), sensors with detection models against target signatures, weapons with ranges and hit or kill probabilities, and a doctrine or rules-of-engagement profile that governs when it fires and emits. The simulation advances in continuous or stepped time with acceleration; contacts are detected, classified, and engaged under that doctrine, often without per-shot player input. Command: Modern Operations, from Warfare Sims, gives operational control of units on a map of Earth through missions or direct orders, runs scenarios lasting hours to days with time acceleration, and draws platforms and weapons from databases such as DB3000; a Professional Edition adds database editing and Monte Carlo analysis for defense customers. Harpoon is the lineage ancestor. Inputs: orders, missions, doctrine settings. Outputs: detections, engagements, losses, and mission outcomes.

The player is a commander, not a pilot. They plan patrols, set emission and engagement rules, manage fuel and munitions, and watch detections develop, so most decisions concern information and timing. Success comes from planning; failure arrives as a missile on the screen that should have been detected earlier.

• fidelity of sensor and signature models
• kill probabilities and countermeasure effects
• doctrine, rules-of-engagement, and emission-control settings available to the player
• database breadth and accuracy
• time acceleration and command granularity (mission versus direct orders)

• High fidelity buries the player in parameters, and new players cannot tell why an engagement failed.
• Database errors or outdated data undermine credibility with expert players.
• Automated unit behavior that ignores doctrine settings reads as the simulation disobeying orders.

• Emission control creates cat-and-mouse play, because radiating sensors reveal the radiating unit.
• Munitions and fuel limits turn engagements into logistics problems over long scenarios.
• Monte Carlo repetition shows outcome distributions, so planning targets probabilities rather than certainties.

• Can reinforcement-learning opponents trained in operational simulators provide credible adversaries without scripted behavior?
• Can language interfaces let players issue operational orders at the level of commander's intent?