In the U.S. Army the variables of the Operational Environment (OE) defined as Political, Military, Economic, Social, Information, Infrastructure, Physical Environment, and Time (PMESII-PT) are used for mission analysis and course of action development. In this research, we discuss how to modify existing simulators in order to add non-kinetic operational variables and investigate how they may shape and influence mission outcomes. We use the StarCraft II (SC2) Learning Environment (LE) which provides an interface for Artificial Intelligent agents to control game entities, gather observations, and adjust actions algorithmically. We develop a military-relevant scenario in SC2LE that will be perturbed by the emergence of non-kinetic challenges that affect the simulation outcome. Finally, we investigate reward functions that leverage the OE context to discover an optimal course of action. By integrating PMESII-PT variables into simulators, this research significantly enhances the realism of military simulations, facilitating the development of algorithms that improve operational planning and decision-making for real-world scenarios.
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