An enhanced massively multi-agent system for discovering HIV population dynamics

Shiwu Zhang*, Jie Yang, Yuehua Wu, Jiming LIU

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)

Abstract

In this paper, we present an enhanced massively multi-agent system based on the previous MMAS for discovering the unique dynamics of HIV infection [1]. The enhanced MMAS keeps the spacial characteristics of cellular automata (CA), and employs mathematical equations within sites. Furthermore, new features are incorporated into the model, such as the sequence representation of HIV genome, immune memory and agent remote diffusion among sites. The enhanced model is closer to the reality and the simulation captures two extreme time scales in the typical three stages dynamics of HIV infection, which make the model more convincing. The simulation also reveals two phase-transitions in the dynamics of the size of immune memory, and indicates that the high mutation rate of HIV is the fatal factor with which HIV destroys the immune system eventually. The enhanced MMAS provides a good tool to study HIV drug therapy for its characterizing the process of HIV infection.

Original languageEnglish
Pages (from-to)988-997
Number of pages10
JournalLecture Notes in Computer Science
Volume3645
Issue numberPART II
DOIs
Publication statusPublished - 2005
EventInternational Conference on Intelligent Computing, ICIC 2005 - Hefei, China
Duration: 23 Aug 200526 Aug 2005

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

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