A Massively Multi-agent System for Discovering HIV-Immune Interaction Dynamics

  • Shiwu Zhang
  • Jiming Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3446)

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.

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References

  1. 1.
    Liu, J., Jin, X.L., Tsui, K.C.: Autonomy Oriented Computing (AOC): From Problem Solving to Complex Systems Modeling. Springer, Heidelberg (2004)Google Scholar
  2. 2.
    Newman, M.E.J.: A Model of Mass Extinction. Santa Fe Institute Working Papers (1997), http://ideas.repec.org/p/wop/safiwp/97-02-013.html
  3. 3.
    Romualdo, P.S., Alessandro, V.: Epidemic Spreading in Scale Free Networks. Physical Review Letters, 3200–3203 (2001)Google Scholar
  4. 4.
    Holland, J.H.: Genetic Algorithm and the Optimal Allocations of Trials. SIAM Journal of Computing 2, 88–105 (1973)MATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Dorigo, M., Caro, G.D.: The Ant Colony Optimization Meta-Heuristic. New Ideas in Optimization, pp. 11–32. McGraw-Hill, New York (1999)Google Scholar
  6. 6.
    Dorigo, M., Caro, G.D., Gambardella, L.M.: Ant Algorithms for Discrete Optimization. Artificial Life 5(2), 137–172 (1999)CrossRefGoogle Scholar
  7. 7.
    Bernardes, A.T., Santos, R.M.: Immunization and Aging: A Learning Process in the Immune Network. Physical Review Letters 81, 3034–3037 (1998)CrossRefGoogle Scholar
  8. 8.
    Santos, R.M.: Immune Responses: Getting Close to Experimental Results with Cellular Automata Models. Annual Reviews of Computational Physics VI, 159–202 (1999)Google Scholar
  9. 9.
    Santos, R., Coutinho, S.: On the Dynamics of the Evolution of HIV Infection (2000), http://arxiv.org/abs/cond-mat/0008081
  10. 10.
    Hershberg, U., Louzoun, Y., Atlan, H., Solomon, S.: HIV Time Hierarchy: Winning the War while. Loosing all the Battles. Physica A 289, 178–190 (2000)MathSciNetGoogle Scholar
  11. 11.
    Morel, P.A.: Mathematical Modeling of Immunological Reactions. Frontiers in Bioscience 3, 338–347 (1998)Google Scholar
  12. 12.
    Louzoun, Y., Solomon, S., Atlan, H., Cohen, I.R.: The Emergence of Spatial Complexity in the Immune System (2000), http://xxx.lanl.gov/abs/nlin.AO/0008133
  13. 13.
    Louzoun, Y., Solomon, S., Atlan, H., Cohen, I.R.: Microscopic Discrete Proliferating Components Cause the Self-organized Emergence of Macroscopic Adaptive Features in Biological Systems (2000), http://xxx.lanl.gov/abs/nlin.AO/0006043
  14. 14.
    Nowak, M.A., Bangham, C.R.M.: Population Dynamics of Immune Responses to Persistent Viruses. Science 272, 74–79 (1996)CrossRefGoogle Scholar
  15. 15.
    Kirschner, D.E., Webb, G.F.: A Mathematical Model of Combined Drug Therapy of HIV Infection. Journal of Theoretical Medicine 1, 25–34 (1997)MATHCrossRefGoogle Scholar
  16. 16.
    Kirschner, D.E., Mehr, R., Perelson, A.S.: Role of the Thymus in Pediatric HIV-1 Infection. Journal of Acquired Immune Deficiency Syndromes and Human Retrovirology 18, 95–109 (1998)Google Scholar
  17. 17.
    Kirschner, D.E.: Using Mathematics to Understand HIV Immune Dynamics. IN: Notices of the American Mathematical Society, pp. 191–202 (1996)Google Scholar
  18. 18.
    Liu, J., Zhang, S.W., Yang, J.: Characterizing Web usage regularities with information foraging agents. IEEE Transactions on Knowledge and Data Engineering 16(5), 566–584 (2004)CrossRefGoogle Scholar
  19. 19.
    Coffin, J.M.: HIV Population Dynamics in Vivo: Implications for Genetic Variation, Pathogenesis, and Therapy. Science 267, 483–489 (1995)CrossRefGoogle Scholar
  20. 20.
    Perelson, A.S., Newmann, A.U., Markowitz, M., Leonard, J.M., Ho, D.D.: HIV-1 Dynamics in Vivo: Virion Clearance Rate, Infected Cell Life-span, and Viral Generation Time. Science 271, 1582–1586 (1996)CrossRefGoogle Scholar
  21. 21.
    Fauci, A.S.: The Immunodeficiency Virus: Infectivity and Mechanisms of Pathogenesis. Science 239, 617–622 (1988)CrossRefGoogle Scholar
  22. 22.
    McCune, J.M.: The Dynamics of CD4+ T-cell Depletion in HIV Disease. Nature 410, 974–979 (2001)CrossRefGoogle Scholar
  23. 23.
    Wei, X., et al.: Viral Dynamics in Human Immunodeficiency Virus Type 1 Infection. Nature 373, 117–122 (1995)CrossRefGoogle Scholar
  24. 24.
    Pennisi, E., Cohen, J.: Eradicating HIV from a Patient: Not Just a Dream? Science 272, 1884 (1996)CrossRefGoogle Scholar
  25. 25.
    Adamic, L.A., Huberman, B.A.: Technical Comment to “Emergence of Scaling in Random Networks”. Science 286(15), 509–512 (1999)MathSciNetGoogle Scholar
  26. 26.
    Nowak, M.A., Anderson, R.M., Boerlijst, M.C., Bonhoeffer, S., May, R.M., McMichal, A.J.: HIV-1 Evolution and Disease Progression. Science 274, 1008–1010 (1996)CrossRefGoogle Scholar
  27. 27.
    Rodrigo, A.G.: HIV Evolutionary Genetics. Proceedings of the National Academy of Sciences 6, 10559–10561 (1999)CrossRefGoogle Scholar
  28. 28.
    Bonhoeffer, S., Holmes, E.C., Nowak, M.A.: Causes of HIV Diversity. Nature 376, 125 (1995)CrossRefGoogle Scholar
  29. 29.
    Wolinsky, S.M., et al.: Adaptive Evolution of Human Immunodeficiency Virus-Type 1 During the Natural Course of Infection. Science 272, 537–542 (1996)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Shiwu Zhang
    • 1
    • 2
  • Jiming Liu
    • 1
  1. 1.Hong Kong Baptist UniversityKowloon Tong, Hong Kong
  2. 2.University of Science and Technology of ChinaChina

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