A framework of evaluating partitioning mechanisms for agent-based simulation systems
SpringSim '09 Proceedings of the 2009 Spring Simulation Multiconference
Technical Section: Emergency crowd simulation for outdoor environments
Computers and Graphics
Crowd modeling and simulation technologies
ACM Transactions on Modeling and Computer Simulation (TOMACS)
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
Cluster based partitioning for agent-based crowd simulations
Winter Simulation Conference
Fuzzy logic injury design for crowd modeling
Proceedings of the 2011 Military Modeling & Simulation Symposium
A multi-agent simulation framework for emergency evacuations incorporating personality and emotions
SETN'10 Proceedings of the 6th Hellenic conference on Artificial Intelligence: theories, models and applications
IVA'12 Proceedings of the 12th international conference on Intelligent Virtual Agents
A multi-methodology agent-based approach for container loading
Proceedings of the Winter Simulation Conference
A simulation model for optimise the fire evacuation configuration in the metro supermarket of hanoi
SEAL'12 Proceedings of the 9th international conference on Simulated Evolution and Learning
Spatial indexing in agent-based crowd simulation
Proceedings of the 6th International ICST Conference on Simulation Tools and Techniques
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Human crowd is a fascinating social phenomenon in nature. This paper presents our work on designing behavior model for virtual humans in a crowd simulation under normal-life and emergency situations. Our model adopts an agent-based approach and employs a layered framework to reflect the natural pattern of human-like decision making process, which generally involves a person's awareness of the situation and consequent changes on the internal attributes. The social group and crowd-related behaviors are modeled according to the findings and theories observed from social psychology (e.g., social attachment theory). By integrating our model into an agent execution process, each individual agent can response differently to the perceived environment and make realistic behavioral decisions based on various physiological, emotional, and social group attributes. To demonstrate the effectiveness of our model, a case study has been conducted, which shows that realistic human behaviors can be generated at both individual and group level. Copyright © 2008 John Wiley & Sons, Ltd.