An agent-based approach for building complex software systems
Communications of the ACM
Validation of Human Behavioral Models
Proceedings of the Twelfth International Florida Artificial Intelligence Research Society Conference
Labeling images with a computer game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Peekaboom: a game for locating objects in images
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
ACM SIGGRAPH 2006 Papers
Computer
Proceedings of the 4th international conference on Knowledge capture
A validation methodology for agent-based simulations
Proceedings of the 2008 ACM symposium on Applied computing
Being a part of the crowd: towards validating VR crowds using presence
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Toward a Generic Framework for Modeling Human Behaviors in Crowd Simulation
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
On the Efficiency of LifeBelt Based Crowd Evacuation
DS-RT '09 Proceedings of the 2009 13th IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications
Validation of agent based crowd egress simulation
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
PLEdestrians: a least-effort approach to crowd simulation
Proceedings of the 2010 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
An agent-based proxemic model for pedestrian and group dynamics: motivations and first experiments
MABS'11 Proceedings of the 12th international conference on Multi-Agent-Based Simulation
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Agent-based modeling as a methodology for understanding natural phenomena is becoming increasingly popular in many disciplines of scientific research. Validation is still a significant problem for agent-based modelers and while various validation methodologies have been proposed, none have been widely adopted. Data plays a key role in the validation of any simulation system, typically large amounts of observable real world data are necessary to compare with model outputs. However, the complex nature of the studied natural systems will often make data collection difficult. This is certainly true for crowd and egress simulation, where data is limited and difficult to collect. In this paper we propose a new technique for validation of agent-based models, particularly those which relate to human behavior. This methodology adopts ideas from the field of Human Computation as a means of collecting large amounts of contextual behavioral data. The key principle is to use games as a means of framing behavioral questions to try and capture people's natural and instinctive decisions. We outline some key design challenges for such games and present one example game in the form of Escape. Escape is an egress based game where people are tasked to escape from rooms inhabited by other people. We show some preliminary studies which highlight some interesting applications of the game in addressing validation of behavioral based crowd and egress simulation.