DocumentCode :
2844501
Title :
Agent-based modelling: a case study in HIV epidemic
Author :
Teweldemedhin, Eyob ; Marwala, Tshilidzi ; Mueller, Conrad
Author_Institution :
Sch. of Comput. Sci., Univ. of the Witwatersrand, Johannesburg, South Africa
fYear :
2004
fDate :
5-8 Dec. 2004
Firstpage :
154
Lastpage :
159
Abstract :
This research presents an agent-based, bottom-up modelling approach to develop a simulation tool for estimating and predicting the spread of the human immunodeficiency virus (HIV) in a given population. HIV is mainly a sexually transmitted disease (STD) causing a serious problem to human health. The virus is transmitted from an infected person to another who was previously healthy through different biological, social and environmental factors. The research develops the simulation tool by modelling these factors by agents. Although research has and is being conducted to estimate and predict the spread of the HIV epidemic, the proposed research seeks to investigate the spread using a different approach. The previous models used a top-down modelling approach. They are built from the general characteristics and behaviours of the population. They have not explored the potential use of agent technology. This research attempts to investigate the flexibility that the multi-agent system offers. Agent-based models are close to the situations that exist in a given real system that consists of autonomous components interacting with each other. The modelling approach has the advantage of observing the interaction made between agents, which is a difficult task in the top-down modelling approach. The research investigates the performance of the tool and presents the first results obtained.
Keywords :
biology computing; diseases; microorganisms; multi-agent systems; HIV epidemic; agent-based modeling; human immunodeficiency virus; multi-agent system; sexually transmitted disease; top-down modelling approach; Africa; Biological system modeling; Computational modeling; Computer aided software engineering; Computer science; Diseases; Human immunodeficiency virus; Mathematical model; Multiagent systems; Predictive models; Multi-agent based simulation; human behaviour; modelling HIV;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Hybrid Intelligent Systems, 2004. HIS '04. Fourth International Conference on
Print_ISBN :
0-7695-2291-2
Type :
conf
DOI :
10.1109/ICHIS.2004.16
Filename :
1409997
Link To Document :
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