Turning anonymous members of a multiagent system into individuals

Inferring a User's Intent on Joining or Passing by Social Groups

“…The remaining four happened outside the social zone (> 3.6m). 6 Flying metaphors can also generate realistic virtual locomotion trajectories [28]. 7 Subjects, e.g., walked around a group (AVD) to join from the other side (JN ).…”

“…Due to, e.g., the entitativity or changes in formation, e.g., based on coherent or incoherent group behavior [35], detecting joins or passby's will be more challenging. Thus, more criteria need to be added to the classification scheme (cp., [6]), e.g., the user's walking speed and the exact trajectory taken in comparison to the group.…”

“…Based on theoretical reports (e.g., [6]), different (social) cues can be used to infer the user's intent to interact with a previously unconsidered VA or social group. Thus, our classification is based on four criteria related to different significant resources in understanding human intentions.…”

“…5(b)) guided them through the pilot study by explaining all tasks. In the familiarization phase, subjects had to navigate to pre-defined locations in the scene to train real walking with the HMD as well as flying via the Vive controller while standing 6 . No body avatar was embedded, however, the correctly positioned virtual representations of the input devices were provided.…”

On the Synergy between Virtual Reality and Multi-Agent Systems

“…Likewise, there are some studies in the field of human movement and behavior that combine both technologies [46][47][48][49][50][51][52][53][54][55][56]. Within this line, the field of crowd simulation has also gained strength, and we also find some studies on it using VR and MAS [57][58][59][60][61][62][63][64][65][66][67][68].…”