Enhancing the behaviorial fidelity of synthetic entities with human behavior models

Human-behavior models (HBMs) and artificial intelligence systems are called on to fill a wide variety of roles in military simulations. Each of the "off the shelf " human behavior models available today focuses on a specific area of human cognition and behavior. While this makes these HBMs very effective in specific roles, none are single-handedly capable of supporting the full range of roles necessary in an urban military scenario involving asymmetric opponents and potentially hostile civilians. The research presented here explores the integration of three separate human behavior models to support three different roles for synthetic participants in a single simulated scenario. The Soar architecture, focusing on knowledge-based, goal-directed behavior, supports a fire team of U.S. Army Rangers. PMFServ, focusing on a physiologically/stress constrained model of decision-making based on emotional utility, supports civilians that may become hostile. Finally, AI.Implant, focusing on individual and crowd navigation, supports a small group of opposing militia. Due to the autonomy and wide range of behavior supported by the three human behavior models, the scenario is more flexible and dynamic than many military simulations and commercial computer games