Controlling individual agents in high-density crowd simulation
SCA '07 Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation
A decision network framework for the behavioral animation of virtual humans
SCA '07 Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation
Virtual Crowds: Methods, Simulation, and Control (Synthesis Lectures on Computer Graphics and Animation)
Modeling Groups of Plausible Virtual Pedestrians
IEEE Computer Graphics and Applications
Directorial Control in a Decision-Theoretic Framework for Interactive Narrative
ICIDS '09 Proceedings of the 2nd Joint International Conference on Interactive Digital Storytelling: Interactive Storytelling
Smart events and primed agents
IVA'10 Proceedings of the 10th international conference on Intelligent virtual agents
Creating customized game experiences by leveraging human creative effort: a planning approach
Agents for games and simulations II
A Behavior-Authoring Framework for Multiactor Simulations
IEEE Computer Graphics and Applications
MIG'11 Proceedings of the 4th international conference on Motion in Games
Stochastic activity authoring with direct user control
Proceedings of the 18th meeting of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games
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This paper describes a framework for controlling the varied activities of groups of background characters (representing extras or supernumeraries). Our platform is built upon an event-centric agent control model, which shifts behavior authoring from writing complex reactive agents to authoring particular activities. This approach allows us to achieve diverse, complex, and collaborative activities while the agents themselves stay simple and generic. An event is defined generically on agent roles, and can be dispatched to any set of agents that can fill those roles. This allows us to control macro-level group behavior with a centralized entity called the Group Coordinator that dispatches events to agents based on their situational and locational context (which can be controlled by an author). What results a structure for controlling macroscopic behavior for groups of background agents.