Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
A Pheromone-Based Utility Model for Collaborative Foraging
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
BOINC: A System for Public-Resource Computing and Storage
GRID '04 Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing
Simulation for the Social Scientist
Simulation for the Social Scientist
Large scale multiagent simulation on the grid
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid - Volume 01
Smooth scaling ahead: progressive MAS simulation from single PCs to grids
MABS'04 Proceedings of the 2004 international conference on Multi-Agent and Multi-Agent-Based Simulation
Behavioral simulations in MapReduce
Proceedings of the VLDB Endowment
Hi-index | 0.00 |
Multi-agent based simulation is an important methodology that uses models incorporating agents to evaluate research conclusions. When the simulation involves a large number of agent, however, it requires extensively high computational power. In that case, all agents in the simulation model should be distributed in a way so that agents can be run in parallel on multiple computational nodes to gain the required performance speed up. In this paper, we present a framework for large scale multi-agent based simulation on grid. We have modified the desktop grid platform BOINC for multi-agent based simulation. Assuming that the agents interact locally with the environment, we proposed an approach to divide the agents for grid nodes so that we can keep load balancing for the distributed simulation while optimizing the communication between grid nodes and the grid server. We have implemented the food foraging simulation to evaluate the feasibility of the framework.