Tears and fears: modeling emotions and emotional behaviors in synthetic agents
Proceedings of the fifth international conference on Autonomous agents
Hierarchical Model for Real Time Simulation of Virtual Human Crowds
IEEE Transactions on Visualization and Computer Graphics
Developments in Standards for Networked Virtual Reality
IEEE Computer Graphics and Applications
Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation
Fast and accurate goal-directed motion synthesis for crowds
Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation
Human behavior models for agents in simulators and games: part I: enabling science with PMFserv
Presence: Teleoperators and Virtual Environments
AI Magazine - Special issue on achieving human-level AI through integrated systems and research
Serious Games for Language Learning: How Much Game, How Much AI?
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
| Hi-index | 0.00 |
This paper explores the problem of effectively simulating realistic populations of background agents in large-scale virtual environments for training and mission rehearsal. It explains why such populations are needed, and surveys the behaviors one would want to see them exhibit. It argues that a successful simulation of a background population ought to be credible, scalable and maintainable, while defining what is meant by those terms. It identifies the key technical challenges as being the efficiency of behavior authoring, and the efficiency of simulation. Finally, it describes some ways such a background population simulation can be verified and validated.