Generalized best-first search strategies and the optimality of A*
Journal of the ACM (JACM)
Creating computer simulation systems: an introduction to the high level architecture
Creating computer simulation systems: an introduction to the high level architecture
An adaptive load balancing method for parallel molecular dynamics simulations
Journal of Computational Physics
Communications of the ACM
Hierarchical Model for Real Time Simulation of Virtual Human Crowds
IEEE Transactions on Visualization and Computer Graphics
Parallel Computing - Special issue: Parallel and nature-inspired computational paradigms and applications
Journal of Computational Physics
An Adaptive Load Management Mechanism for Distributed Simulation of Multi-agent Systems
DS-RT '05 Proceedings of the 9th IEEE International Symposium on Distributed Simulation and Real-Time Applications
Computer Animation and Virtual Worlds - CASA 2006
Real-time navigating crowds: scalable simulation and rendering: Research Articles
Computer Animation and Virtual Worlds - CASA 2006
Analysing movement and world transitions in virtual reality tele-conferencing
ECSCW'97 Proceedings of the fifth conference on European Conference on Computer-Supported Cooperative Work
Distributed simulation of agent-based systems with HLA
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Agent-based human behavior modeling for crowd simulation
Computer Animation and Virtual Worlds - CASA'2008 Special Issue
A framework of evaluating partitioning mechanisms for agent-based simulation systems
SpringSim '09 Proceedings of the 2009 Spring Simulation Multiconference
A distributed framework for scalable large-scale crowd simulation
ICVR'07 Proceedings of the 2nd international conference on Virtual reality
Grid-based partitioning for large-scale distributed agent-based crowd simulation
Proceedings of the Winter Simulation Conference
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Simulating crowds is a challenging but important problem. There are various methodologies in the literature ranging from macroscopic numerical flow simulations to detailed, microscopic agent simulations. One key issue for all crowd simulations is scalability. Some methods address this issue through abstraction, describing global properties of homogeneous crowds. However, ideally a modeler should be able to simulate large heterogeneous crowds at fine levels of detail. We are attempting to achieve scalability through the application of distributed simulation techniques to agent-based crowd simulation. Distributed simulation, however, introduces its own challenges, in particular how to efficiently partition the load between a number of machines. In this paper we introduce a method of partitioning agents onto machines using an adapted k-means clustering algorithm. We present, validate and use an analysis tool to compare the proposed clustered partitioning approach with a series of existing methods.