Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/48602
Title: Large-scale agent simulation of agent-based models
Authors: Poh, Wei Li.
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling
Issue Date: 2012
Abstract: Agents are a very useful form of modelling and understanding complex natural systems. Agent-based simulations have been applied in many different domains, such as: economics, sociology, psychology, etc. While they offer a very flexible approach to modeling such systems, they often require significant computational resources for execution. Usually, distributed computing techniques are widely used in the simulation and modeling of agents in order to reduce simulation or computational time. There are mainly 3 factors that affect computational time: node-to-node communication cost, migration cost of agents and the load of each node. Depending on the type of partition methods used, it would affect the nodes communication cost and the node’s load in which may impact to the simulation time. This project will investigate the effectiveness of different partition methods for distributed simulation of agent-based models (ABM) in discrete and continuous environments. The intention is to provide faster execution of the models. Case studies example used for discrete environment is Game of Life model (GoL) and Boids model for continuous environment. The results find that static partitioning of environment horizontally (SPH) provided the fastest execution time for discrete environment. For continuous environment, depending on the behavior of the agents, static partitioning of environment vertically (SPV) or grid-based partitioning may provide the fastest execution time.
URI: http://hdl.handle.net/10356/48602
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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