Command Agents with Human-Like Decision Making Strategies

Human behavior representation in military simulations is not sufficiently realistic, specially the decision making by synthetic military commanders. In order to address some of these deficiencies, we have developed a computer implementation of Recognition Primed Decision Making (RPD) model using Soar cognitive architecture and it is referred to as RPD-Soar agent in this paper. The proposed implementation is evaluated using prototypical scenarios arising in command decision making in tactical situations. Due to the ability of the RPD-Soar agent to mentally simulate applicable courses of action it is possible to use the agent without further training. These agents can be further enhanced to exhibit various levels of expertise. The preliminary results clearly demonstrate the ability of the model to represent human behavior variability within and across individuals. The results also show the change in decision making strategy with experience.