Dynamic Behavior Variation in Virtual Human Agents Driven by a Model of Needs and Personality

In this paper we expand on creating dynamically differing animations from single stock animations. This is done using Markov's hierarchy of needs in conjunction with the OCEAN personality model. On start, animations are augmented based on a virtual human agent's parameters from the previous two models. Where Markov's decreases with time, and OCEAN remains static. In our findings this adds more subtle realism to the virtual agent overall and breaks the mirroring effect when agents use the same animations. The subtle changes in the model can be hard to discern unless looking for it. However, we can conclude that this subtle increase in realism has more potential when used in VR settings. Due to the closeness that users will interact with virtual human agents, these subtle changes become more apparent.