Boosting the immune system

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5132 LNCS, Issue , 2008, Pages 316-327

  McEwan, Chris ^a   Hart, Emma ^a   Paechter, Ben ^a  

^a EDINBURGH NAPIER UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER NETWORKS; DYNAMICAL SYSTEMS; MATHEMATICAL MODELS; ROBOT LEARNING; SCHRODINGER EQUATION;

INTERNATIONAL CONFERENCES; MACHINE-LEARNING;

IMMUNOLOGY;

EID: 51049107972     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-85072-4_28     Document Type: Conference Paper

References (19)

1. Aggarwal, C.C., Hinneburg, A., Keim, D. A.: On the surprising behavior of distance metrics in high dimensional space. In: Van den Bussche, J., Vianu, V. (eds.) ICDT 2001. LNCS, vol. 1973. Springer, Heidelberg (2000)
2. Beyer, K., Goldstein, J., Ramakrishnan, R., Shaft, U.: When is "nearest neighbor" meaningful? In: Beeri, C., Bruneman, P. (eds.) ICDT 1999. LNCS, vol. 1540, pp. 217-235. Springer, Heidelberg (1998)
3. Carneiro, J., Coutinho, A., Faro, J., Stewart, J.: A model of the immune network with b-t cell co-operation, i - prototypical structures and dynamics. Journal of Theoretical Biology 182, 513-529 (1996)
4. Carneiro, J., Coutinho, A., Stewart, J.: A model of the immune network with b-t cell co-operation, ii - the simulation of ontogenisis. Journal of Theoretical Biology 182, 531-547 (1996)
5. Carneiro, J., Stewart, J.: Rethinking shape space: Evidence from simulated docking suggests that steric shape complementarity is not limiting for antibody-antigen recognition and idiotypic interactions. J. Theor. Biol. 169, 391-402 (1994)
6. Cohen, I.R., Segel, L.A.: Design Principles for the Immune System and Other Distributed Autonomous Systems. Oxford University Press, Oxford (2001)
7. Ferrer, R., Cancho, I., Sole, R.: The small-world of human language. In: Proceedings of the Royal Society of London (2001)
8. Freund, Y., Schapire, R.E.: A decision theoretic generalisation of on-line learning and an application to boosting. Journal of Computer and System Sciences 55(1), 119-139 (1997)
9. Friedman, J.H.: On bias variance 0-1 loss and the curse-of- dimensionality. Data Min. Knowl. Discov. 1, 55-77 (1997)
10. Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning. Springer, Heidelberg (2001)
11. Janeway, C.A., Travers, P., Walport, M., Schlomchik, M.: Immunobiology, Garland (2001)
12. Jeme, N.K.: The generative grammer of the immune system. Nobel Lecture (1984)
13. Mcewan, C., Hart, E., Paechter, B.: Revisiting the central and peripheral immune system. In: de Castro, L.N., Von Zuben, F.J., Knidel, H. (eds.) ICARIS 2007. LNCS, vol. 4628. Springer, Heidelberg (2007)
14. McEwan, C., Hart, E., Paechter, B.: Towards a model of immunological tolerance and autonomous learning. Natural Computing (submitted, 2008)
15. Barabasi, A.-L., Oltvai, Z.N.: Network biology: Understanding the cell's functional organization. Nature Reviews Genetics 5, 101-113 (2004)
16. Stewart, J., Carneiro, J.: Artificial Immune Systems and their Applications. In: The central and the peripheral immune system: What is the relationship?, pp. 47-64. Springer, Heidelberg (1998)
17. Stibor, T., Timmis, J., Eckert, C.: On the use of hyperspheres in artificial immune systems as antibody recognition regions. In: Bersini, H., Carneiro, J. (eds.) ICARIS 2006. LNCS, vol. 4163. Springer, Heidelberg (2006)
18. Timmis, J., Andrews, P., Owens, N., Clark, E.: An interdisciplinary perspective on artificial immune systems. Evolutionary Intelligence 1(1), 5-26 (2008)
19. Varela, F.J., Coutinho, A.: Second generation immune networks. Immunology Today 12(5), 159-166 (1991)