Modeling believable game characters

The behavior of virtual characters in computer games is usually determined solely by decision trees or finite state machines, which is detrimental to the characters' believability. It has been argued that enhancing the virtual characters with emotions, personalities, and moods, may make their behavior more diverse and thus more believable. Most research in this direction is based on existing (socio-)psychological literature, but not tested in a suitable experimental setting where humans interact with the virtual characters. In our research, we use a simplified version of the personality model of Ochs et al. [1], which we test in a game which has human participants interact with three agents with different personalities: an extraverted agent, a neurotic agent, and a neutral agent. The model only influences the agents' emotions, which are only exhibited by their facial expressions. The participants were asked to assess the agents' personality based on six possible traits. We found that the participants considered the neurotic agent as the most neurotic, while there are also indications that the extraverted agent was considered the most extraverted. We conclude that players will indeed distinguish personality differences between agents based on their facial expression of emotions. Therefore, using a personality model may make it easy for game developers to quickly create a high variety of virtual characters, who exhibit individual behaviors, making them more believable.