Spontaneous Avatar Behaviour for Social Territoriality

The challenge of making a virtual world believable includes a requirement for AI entities which autonomously react to a dynamic environment. After the breakthroughs in believability introduced by modern lightning and physics techniques, the focus is shifting to better AI behaviour sophistication. Avatars and agents in a realistic virtual environment must exhibit a certain degree of presence and awareness of the surrounding, reacting consistently to unexpected contingencies and contextual social situations. Unconscious reactions serve as evidence of life, and can also signal social availability and spatial awareness to others. These behaviours get lost when avatar motion requires explicit user control. This thesis presents new AI technology for generating believable social behaviour in avatars. The focus is on human territorial behaviours during social interactions, such as during conversations, gatherings and when standing in line. Driven by theories on human face-to-face interaction and territoriality, we combine principles from the field of crowd simulators with a steering behaviours architecture to define a reactive framework which supports avatar group dynamics during social interaction. This framework manages a set of prioritized behaviours updated at various frequencies, which can be combined in different ways. This approach provides enough flexibility to model the territorial dynamics of social interactions as a set of social norms that constrain the avatar’s reactivity. The resulting social group behaviour appears relatively robust, but perhaps more importantly, it starts to bring a new sense of relevance and continuity to the virtual bodies that often get separated from the simulated social situation. Ósjálfráð félagsleg svæðishegðun fyrir avatara