Optimizing Algorithmic Decisions in Executive Game Simulations

We model an algorithmic opponent player for a game simulation of the use-case of cyber espionage for the purpose of training executives that lack technical proficiency preparing for the implementation of the NIS2 directive in EU member states. In the first part of the paper, we lay out the common practices of developing an algorithmic opponent player suggested by a strong body of literature in the field of game simulations. We formally validate the decision logic of the opponent player for the game simulation and argue the decisions to simulate relevant, rational, and realistic behavior. In the second part, we explain our model that demonstrates the functionality, behavior and decision sequence of our proposed algorithmic opponent player in an executive game simulation. Finally, we discuss avenues for game development.