Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Evaluating computer-supported cooperative work: models and frameworks
CSCW '04 Proceedings of the 2004 ACM conference on Computer supported cooperative work
ACM SIGGRAPH 2006 Papers
Articulating common ground in cooperative work: content and process
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Modeling Groups of Plausible Virtual Pedestrians
IEEE Computer Graphics and Applications
Aggregate dynamics for dense crowd simulation
ACM SIGGRAPH Asia 2009 papers
Evaluation of virtual agents utilizing theory of mind in a real time action game
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Modeling Human-Like Decision Making for Virtual Agents in Time-Critical Situations
CW '10 Proceedings of the 2010 International Conference on Cyberworlds
Culture-related differences in aspects of behavior for virtual characters across Germany and Japan
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
ESCAPES: evacuation simulation with children, authorities, parents, emotions, and social comparison
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Modeling social groups in crowds using common ground theory
Proceedings of the Winter Simulation Conference
Message passing without send-receive
Future Generation Computer Systems - Parallel computing technologies (PaCT-2001)
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This paper presents a multi-agent model for large crowd simulations that addresses the need for socially plausible coordination behavior. A computational model for multi-agent coordination informed by well-established common ground theory is proposed. We introduce the idea of macro- and micro-coordination strategies that allow agent-based simulations to adapt to different domains. Our agent model allows the selection of appropriate behaviors based on the spatiotemporal conditions of the agent-group's environment. By showing that different micro-coordination strategies of individual groups has an influence on the overall distribution of a crowd, we demonstrate the importance of incorporating such models into multi-agent simulations of large crowd behaviors.