Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
A Multi-Agent Cellular Automata System for Visualising Simulated Pedestrian Activity
Proceedings of the Fourth International Conference on Cellular Automata for Research and Industry: Theoretical and Practical Issues on Cellular Automata
MASON: A Multiagent Simulation Environment
Simulation
Experiences creating three implementations of the repast agent modeling toolkit
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Data parallel execution challenges and runtime performance of agent simulations on GPUs
Proceedings of the 2008 Spring simulation multiconference
Using neural networks and cellular automata for modelling intra-urban land-use dynamics
International Journal of Geographical Information Science
LifeBelt: Silent Directional Guidance for Crowd Evacuation
ISWC '09 Proceedings of the 2009 International Symposium on Wearable Computers
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
Parallel cellular automata for large-scale urban simulation using load-balancing techniques
International Journal of Geographical Information Science
LifeBelt: Crowd Evacuation Based on Vibro-Tactile Guidance
IEEE Pervasive Computing
Comparing Parallel Simulation of Social Agents Using Cilk and OpenCL
DS-RT '11 Proceedings of the 2011 IEEE/ACM 15th International Symposium on Distributed Simulation and Real Time Applications
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Due to catastrophic disasters induced by forces of nature like flooding or tsunamis, terrorism or nuclear power plant accidents, understanding the dynamics of urban evacuation systems has elicited massive interest over the past years. While discrete event simulations of evacuation models become prohibitively complex dealing with the time, space and individual behavior, multiagent based models have revealed to be a potentially more effective. This paper introduces models of configurations of social agents at a massive scale, which, together with the most recent supercomputing technology, allows for a simulation analysis of realistic evacuation models at the level of large cities ($10^6-10^8$ agents). Agent based models of demographics and the morphology of cities together with population densities, mobility patterns, individual decision making, and agent interactions are implemented into a tool chain which ultimately generates Repast HPC code, which is then executed on a 2,048 node shared memory multiprocessor server (SGI Altix UV-1000). We demonstrate how different evacuation strategies can be assessed based on costly, yet feasible simulation runs--thus evidencing, that a whole class of demanding, very complex simulation problems has found a convincing solution.