Abstract
In this position paper, we outline a vision for a new type of engineering: immuno-engineering, that can be used for the development of biologically grounded and theoretically understood Artificial Immune Systems (AIS). We argue that, like many bio-inspired paradigms, AIS have drifted somewhat away from the source of inspiration. We also argue that through an interdisciplinary approach, it is possible to exploit the underlying biology for computation in a way that, as yet, has not been achieved. Immuno-engineering will not only allow for the potential development of more powerful AIS, but allow for feed back to biology from computation.
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Timmis, J., Andrews, P.S., Owens, N., Clark, E.: An interdisciplinary perpective on artificial immune systems. Evolutionary Intelligence 1(1) (2008) 5-26
Cohen, I.R.: Real and artificial immune systems: Computing the state of the body. Imm. Rev. 7 (July 2007) 569-574
. de Castro, L.N., Timmis, J.: Artificial Immune Systems: A New Computational Intelligence Approach. Springer (2002)
Forrest, S., Perelson, A., Allen, L., R.Cherukuri: Self-nonself discrimination in a computer. In: IEEE Symposium on Research in Security and Privacy, Los Alamos, CA, IEEE Computer Society Press (1994)
. Ishida, Y.: Fully distributed diagnosis by pdp learning algorithm: Towards immune network pdp model. In: Proc. of the Int. Joint Conf. on Neural Networks. (1990) 777-782
Bersini, H., Varela, F.J.: Hints for adaptive problem solving gleaned from immune networks. In Schwefel, H., Manner, R., eds.: Proc. of the First Conference on Parallel Problem Solving from Nature. Springer-Verlag, Berlin, Germany (1991)
. Timmis, J., Bentley, P.J., eds.: Proceedings of the 1st International Conference on Artificial Immune Systems (ICARIS 2002), University of Kent Printing Unit (2002)
. Timmis, J., Bentley, P., Hart, E., eds.: Proceedings of the 2nd International Conference on Artificial Immune Systems (ICARIS 2003), LNCS 2787, Springer (2003)
Nicosia, G., Cutello, V., Bentley, P.J., Timmis, J., eds.: Proceedings of the 3rd International Conference on Artificial Immune Systems (ICARIS 2004). LNCS 3239, Springer (2004)
. Jacob, C., Pilat, M., Bentley, P., Timmis, J., eds.: Proc. of the 4th International Conference on Artificial Immune Systems (ICARIS). Volume 3627 of Lecture Notes in Computer Science., Springer (2005)
Bersini, H., Carneiro, J., eds.: Proc. of 5th International Conference on Artificial Immune Systems. Lecture Notes in Computer Science, Springer (2006)
de Castro, L.N., Von Zuben, F.J., Knidel, H., eds.: Proceedings of the 6th International Conference on Artificial Immune Systems. Volume 4628 of Lecture Notes in Computer Science. Springer (2007)
. Dasgupta, D., ed.: Artificial Immune Systems and their Applications. Springer (1999)
. de Castro, L.N., Von Zuben, F.J.: Artificial immune systems: Part I—basic theory and applications. Technical Report DCA-RT 01/99, School of Computing and Electrical Engineering, State University of Campinas, Brazil (1999) 2 http://www.bioinspired.com/research/xArcH/index.shtml
de Castro, L.N., Von Zuben, F.J.: Artificial immune systems: Part II—a survey of applications. Technical Report DCA-RT 02/00, School of Computing and Electrical Engineering, State University of Campinas, Brazil (2000)
. Ji, Z., Dasgupta, D.: Artificial immune system (AIS) research in the last five years. In: Congress on Evolutionary Computation. Volume 1., Canberra, Australia, IEEE (December 8-12 2003) 123-130
Garrett, S.: How do we evaluate artificial immune systems? Evolutionary Computation 13(2) (2005) 145-177
Timmis, J.: Artificial immune systems: Today and tomorow. Natural Computing 6(1) (Feb. 2007) 1-18
. Timmis, J., Knight, T.: Artificial immune systems: Using the immune system as inspiration for data mining. In: Data Mining: A Heuristic Approach. Idea Group (2001) 209-230
. Kim, J., Bentley, P., Aickelin, U., Greensmith, J., Tedesco, G., Twycross, J.: Immune system approaches to intrusion detection - a review. Natural Computing in print (2007)
. Hart, E., Timmis, J.: Application areas of AIS: The past, the present and the future. Applied Soft Computing 8(1) (2008) 191-201 In Press, Corrected Proof, Available online 12 February 2007.
. Timmis, J., Hone, A., Stibor, T., Clark, E.: Theoretical advances in artificial immune systems. Journal of Theoretical Computer Science In press(doi:10.1016/j.tcs.2008.02.011) (2008)
Forrest, S., Beauchemin, C.: Computer Immunology. Immunol. Rev. 216(1) (2007) 176-197
de Castro, L.N., Von Zuben, F.J.: Learning and optimization using the clonal selection principle. IEEE Transactions on Evolutionary Computation 6(3) (2002) 239-251
Gonzalez, F.A., Dasgupta, D.: Anomaly detection using real-valued negative selection. Genetic Programming and Evolvable Machines 4(4) (2003) 383-403
. Neal, M.: Meta-stable memory in an artificial immune network. [8] 168-180
. Greensmith, J., Aickelin, U., Cayzer, S.: Introducing dendritic cells as a novel immune- inspired algorithm for anomaly detection. [10]
. Aickelin, U., Bentley, P., Cayzer, S., Kim, J., McLeod, J.: Danger theory: The link between AIS and IDS? [8] 147-155
. Bentley, P.J., Greensmith, J., Ujjin, S.: Two ways to grow tissue for Artificial Immune Sys-tems. [10] 139-152
. Twycross, J., Aickelin, U.: Towards a conceptual framework for innate immunity. [10] 112- 125
. Greensmith, J., Aickelin, U., Twycross, J.: Articulation and clarification of the dendritic cell algorithm. [46] 404-417
. Orosz, M.: An Introduction to Immuno-Ecology and Immuno-Informatics. In: Design Principles from the Immune System. Sante Fe (2001) 125-150
Stepney, S., Smith, R., Timmis, J., Tyrrell, A., Neal, M., Hone, A.: Conceptual frameworks for artificial immune systems. Int. J. Unconventional Computing 1(3) (2006) 315-338
Freitas, A., Timmis, J.: Revisiting the foundations of artificial immune systems for data mining. IEEE Trans. Evol. Comp. 11(4) (2007) 521-540
. Milner, R.: Communicating and Mobile Systems: the π -Calculus. Cambridge University Press (1999)
. Phillips, A., Cardelli, L.: Efficient, correct simulation of biological processes in the stochas- tic pi-calculus. In: Proceedings of Computational Methods in Systems Biology (CMSB’07). Volume 4695. (2007) 184-199
Alon, U.: Uri alon, network motifs: theory and experimental approaches. Nature Reviews Genetics 8 (2007) 450-461
. Gamma, E., Helm, R., Johnson, R., Vlissides, J.: Design Patterns. Addison Wesley (1995)
Sachs, K., Perez, O., Pe’er, D., Lauffenburger, D., Nolan, G.: Causal protein-signaling networks derived from multiparameter single-cell data. Science 308 (2005) 523-529
. Steinman, L.: A brief history of t(h)17, the first major revision in the t(h)1/t(h)2 hypothesis of t cell-mediated tissue damage. Nature Medicine (2007) 139-145
. Hart, E., Timmis, J.: Application areas of AIS: The past, the present and the future. [10] 483-497
. Owens, N., Timmis, J., Greensted, A., Tyrrell, A.: On immune inspired homeostasis for electronic systems. [12] 216-227
. Davoudani, D., Hart, E., Paechter, B.: An immune-inspired approach to speckled computing. [12] 288-299
. Guzella, T., Mota-Santos, T., Caminhas, W.: Towards a novel immune inspired approach to temporal anomaly detection. [12] 119-130
. Bersini, H.: Immune system modeling: The OO way. [46] 150-163
Bersini, H., Carneiro, J., eds.: Proceedings of the 5th International Conference on Artificial Immune Systems. Volume 4163 of LNCS. Springer (2006)
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Timmis, J. et al. (2008). Immuno-engineering. In: Hinchey, M., Pagnoni, A., Rammig, F.J., Schmeck, H. (eds) Biologically-Inspired Collaborative Computing. BICC 2008. IFIP – The International Federation for Information Processing, vol 268. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-09655-1_2
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DOI: https://doi.org/10.1007/978-0-387-09655-1_2
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