Synthetic entities in military simulations often fall short of expectations. They rely on rule-based or reactive computational models, which are minimally intelligent and incapable of adapting based on experience. Even at that current level, they are costly to create and take time to develop.
To create more effective synthetic entities, we need adaptive models that demonstrate human-like behavior—entities that can communicate, perceive their environment, reason, and choose actions dynamically. Experiential learning is key to building such credible behavior; trying to program realism entirely through pre-defined rules would be highly impractical.