A massively multi-agent system for discovering HIV-immune interaction dynamics

Shiwu Zhang*, Jiming LIU

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

In MMAS-based biological system simulation, it is a challenging task to deal with numerous interactions among a vast number of autonomous agents. In our work, a hybrid massively multi-agent systems (MMAS) model is developed, and it incorporates the characteristics of cellular automaton (CA) and system-level mathematical equation modeling to simulate HIV-immune interaction dynamics. The mathematical equations are adopted within the site of a two-dimensional lattice. As the average high density, agent interactions can be calculated according to the equations without significantly affecting the performance of the systems studied. In the mean time, the CA model keeps the spatial characteristics of HIV evolution among the sites. The simulation based on the implemented MMAS discovers the dynamics of HIV evolution over different temporal and spatial scales, and reproduces the typical three-stage dynamics of HIV infection.

Original languageEnglish
Title of host publicationMassively Multi-Agent Systems I - First International Workshop, MMAS 2004, Revised Selected and Invited Papers
PublisherSpringer Verlag
Pages161-173
Number of pages13
ISBN (Print)3540269746, 9783540269748
DOIs
Publication statusPublished - 2005
Event1st International Workshop on Massively Multi-Agent Systems, MMAS 2004 - Kyoto, Japan
Duration: 10 Dec 200411 Dec 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3446 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Workshop on Massively Multi-Agent Systems, MMAS 2004
Country/TerritoryJapan
CityKyoto
Period10/12/0411/12/04

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

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