Military Training & Simulation

Wargaming software supports structured analytical exercises where commanders and staff explore courses of action (COAs), test operational plans against adversary responses, and develop tactical proficiency. It is used for: operational planning (testing plan assumptions before execution); force development (evaluating new doctrine, organizations, or equipment); training (decision-making under time pressure); and experimentation (exploring emerging concepts in multi-domain operations). AI-driven wargaming tools like WARG accelerate scenario generation and provide immediate analytical feedback on decisions.

HLA is the standard interoperability framework for federating military simulations into a combined exercise – defined in IEEE 1516. Each simulator or simulation system is an HLA federate; the Runtime Infrastructure (RTI) coordinates data exchange between federates according to a Federation Object Model (FOM) that defines what data is shared and how. HLA enables simulators from different vendors and nations to interoperate in a single distributed exercise, which is essential for coalition training events.

DIS (IEEE 1278) is an older but still widely deployed protocol for real-time distribution of entity state information – position, velocity, orientation, appearance, and weapons fire – between simulation systems. DIS uses broadcast UDP packets (PDUs – Protocol Data Units) to update all participants about each entity's state. While HLA provides more flexibility for complex federations, DIS remains the baseline interoperability protocol for many legacy military simulation systems and is often supported alongside HLA in modern platforms.

An AAR system captures exercise data – entity positions, events, decisions, and communications – throughout a training event and replays it for review by commanders, trainers, and participants. A good AAR system synchronizes the replay timeline with recorded radio communications and decision logs, allows trainers to annotate events and highlight teaching points, and generates structured performance metrics. AARs are the primary learning mechanism in simulation-based training – the quality of the AAR system directly determines training effectiveness.

VR (Virtual Reality) training immerses individual operators in a synthetic 3D environment using head-mounted displays, haptic controllers, and positional tracking – enabling skills practice for complex tasks like vehicle operations, urban combat room clearing, or casualty care. VR training is particularly effective for high-risk procedures that cannot be safely rehearsed in live environments, and for building muscle memory in tasks that require repetition. Modern defense VR training platforms integrate with AI OpFor and federation frameworks for multi-player scenarios.

Scripted scenarios follow a fixed sequence regardless of trainee decisions – a trainee who discovers the script can optimize for it rather than developing genuine decision-making skills. AI-driven scenario generation adapts the scenario in real time to trainee actions: adversary forces respond tactically, unexpected events are introduced when the trainee stalls, and scenario complexity scales with trainee proficiency. This ensures training value is maintained across multiple repetitions and prevents scenario exploitation. WARG uses AI to generate and adapt multi-domain scenarios dynamically.

Corvus Intelligence designs and builds wargaming platforms, multi-domain scenario simulators, and after-action review tools for NATO forces and allied defense organizations. WARG – Corvus Intelligence's training product – provides AI-powered multi-domain operations simulation across land, maritime, air, space, and cyberspace with instant AI-generated scenarios and decision analysis. Bespoke simulation development services cover HLA/DIS federate development, AI OpFor engineering, VR training environment integration, and scenario design tooling.

WARG is Corvus Intelligence's AI wargaming platform for multi-domain military exercises. It replaces static scenario planning with infinite AI-generated multi-domain wargaming scenarios that adapt to player tactics in real-time, enabling commanders and staff to train decision-making across land, maritime, air, space, and cyberspace domains without scripted constraints.

WARG's AI engine generates and adapts wargaming scenarios across land, maritime, air, space, and cyberspace domains based on real-time player decisions. Rather than following a fixed script, the engine observes player actions and continuously reshapes the scenario – adjusting adversary posture, introducing new events, and scaling complexity – so that training value is preserved across repeated exercises and scenario exploitation is prevented.