The goal of this project is to model and study large populations of humans by simulating small-scale social interactions that take into account social influence dynamics, human behaviors, cognitive science, artificial intelligence, and social science. We aim to support a variety of applications, such as examining the implications of social science theories and developing playable, explorable story worlds. We support novice and experienced researchers and game designers with the design of a multi-agent simulation frameworks, authoring tools, and engines capable of complex simulation of societies of social, digital humans.
Agent-based social simulation can be useful for creating digital twins of societies of interacting autonomous agents. Such simulations are useful for testing hypotheses about behaviour and belief change in the presence of interventions. In this …
This proposal describes our efforts to evaluate and operationalize a taxonomy and an accompanying framework or ``social physics engine''. Our taxonomy and accompanying framework would allow scientists to reproduce and evaluate existing models, collaborate on standards, share advances with other researchers and practitioners, allow for better communication and methodologies developed for new techniques, and allow for a more rigorous model-to-model analysis.
Bolstered by a growing interest in simulating believable non-player characters (NPCs), work on NPC models has spanned topics such as planning, procedural storytelling, decision-making, and social dynamics. However, research groups work in isolation, …
This work expands on and extends work previously pubished for the Lyra System towards the Ph.D. Computer Science qualifier requirement at NC State University. We conducted a human-subjects study of Lyra to evaluate the generated conversations and …
Lyra is a simulation of a opinionated population of virtual characters with inherent biases that can believably debate politically-charged topics. We conducted a human-subjects study to evaluate these generated conversations and affinity groups for their believability and to inform future iterations of the simulation. We believe successful simulation of opinion change in social dynamics provides a foundation for computational recognition, prediction, and interfacing with humans.