Artificial intelligence is used in video games for controlling AI agents but often follow a static pre-defined behaviour. An AI capable of online learning would be able to adapt their behaviour to whatever they may encounter. ‘Dynamic scripting’ is one such technique designed to be used in games with random outcomes. This study seeks to examine if there is a measurable difference in the learning efficiency of dynamic scripting between games with stochastic outcomes and those with deterministic outcomes. A CRPG was made with dynamic scripting implemented in charge of a team of AI agents and a toggle to force deterministic or stochastic game rules. A series of encounters against a static AI was then performed until the dynamic team was deemed effective enough and the learning efficiency measured by how long this took. The results suggest a difference favouring dynamic scripting in deterministic environments.