publication . Article . 2004

Sobre un Modelo Computacional del Sistema Inmune

Monroy, Raúl; Saab, Rosa; Godínez, Fernando;
Open Access English
  • Published: 01 Jun 2004
  • Publisher: Centro de Investigación en computación, IPN
Immune systems of live forms have been an abundant source of inspiration to contemporary computer scientists. Problem solving strategies, stemming from known immune system phenomena, have been successfully applied to challenging problems of modern computing. However, research in artificial immune systems has overlooked establishing a coherent model of known immune system behaviour. This paper aims reports on an preliminary computer model of an immune system, where each immune system component is specified in terms of its observable behaviour using a suitable process algebra. Our model is not only suitable to simulation but also and more importantly to formal ana...
free text keywords: Multiagent systems and Distributed AI, Immunology, Immune Based Computer Systems, Sistemas Multiagentes y AI Distribuida, Inmunología, Sistemas de Cómputo basado en Inmunidad
27 references, page 1 of 2

[1] R. Belew and S. Forrest. Learning classifier systems, from foundations to applications. In, P.L. Lanzi, W. Stolzmann, and W.Wilson S, editors, Proceedings of IWLCS '99, volume 1813 of Lecture Notes in Computer Science. Springer, 2000.

[2] J. A. Bergstra and J.W. Klop. Algebra of communicating processes with abstraction. Theoretical Compute Science, 37(1):77⎯121, 1985. [OpenAIRE]

[3] D. Dasgupta. Artificial Immune System and Their Applications. Springer, U.S.A.,1998.

[4] P. De Haeseleer, S. Forrest, and P. Helman. An immunological approach to change detection: Algorithms analysis an implications. In Proceedings of the 1996 IEEE Symposium on Research in Security and Privacy, pages 110⎯119. IEEE Computer Society Press, 1996.

[5] S.Forrest, S.A. Hofmeyr, and A. Somayaji. Computer immunology. Communications of the Association for Computing Machinery, 40(10):88⎯96, 1997. [OpenAIRE]

[6] S. Gilmore, J. Hillston, and M. Ribaudo. An efficient algorithm for aggregating PEPA models. IEEE Transactions on Software Engineering, 27(5):449⎯464, May 2001. [OpenAIRE]

[7] M.J. Hatcher, A.M. Dunn, and C. Tofts. The effect of the embryonic bottleneck on vertically transmitted parasites. In Proceedings of 1st International Conference on Information Processing in Cells and Tissues, page In Press. University of Liverpool, 1996.

[8] M.J. Hatcher and C. Tofts. The effect of point of expression on ESS sex ratios. Journal of Theoretical Biology, 175:263⎯266, 1995.

[9] M.J. Hatcher and C.Tofts. The evolution of polygenic sex determination with potential for environmental manipulation. Technical Report Series, Department of Computer Science, UMCS-95-4-2, University of Manchester, 1995.

[10] M. Hennessy and H. Lin. Proof systems for message passing process algebras. Formal Aspects of Computing, 8(4):379⎯407, 1996. Also available from Sussex as Computing Science Technical Report 3/93.

[11] Jane Hillston. A Compositional Approach to Performance Modelling. Cambridge University Press, 1996.

[12] C.A.R. Hoare. Communicating sequential processes. Communications of the Association for Computing Machinery, 21(8):666⎯77, 1978. [OpenAIRE]

[13] S. Hofmeyr and S. Forrest. Architecture for an artificial immune system. Evolutionary Computation Journal, 8(4):443⎯473, 2000. [OpenAIRE]

[14] ISO. Information processing systems⎯Open systems interconnection. LOTOS⎯A formal description technique based on the temporal ordering of observational behaviour. ISO 8807, 1989.

[15] R. López, F. Díaz, and S. Arias. Biología Celular. Editorial Iberoamérica, México, 1991.

27 references, page 1 of 2
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