Basic technologies for knowledge transfer in intelligent systems

Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007

Volumn , Issue , 2007, Pages 251-258

  Buchtala, Oliver ^a   Sick, Bernhard ^a  

^a UNIVERSITY OF PASSAU   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); CLUSTERING ALGORITHMS; INTELLIGENT AGENTS; KNOWLEDGE ENGINEERING; OPTIMIZATION; TECHNOLOGY TRANSFER;

ARTIFICIAL SYSTEMS; HUMAN EVOLUTION; ONTOGENY;

INTELLIGENT SYSTEMS;

EID: 34548757259     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ALIFE.2007.367804     Document Type: Conference Paper

References (13)

1. C. Müller-Schloer and B. Sick, "Emergence in organic computing systems: Discussion of a controversial concept," in Autonomic and Trusted Computing, Proceedings of the 3rd International Conference ATC-06, Wuhan, ser. LNCS, L. T. Yang, H. Jin, J. Ma, and T. Ungerer, Eds., no. 4158. Springer Verlag, Berlin, Heidelberg, New York, 2006, pp. 1-16.
2. L. A. Zadeh, "What is soft computing?" Soft Computing - A Fusion of Foundations, Methodologies and Applications, vol. 1, no. 1, p. 1, 1997.
3. O. Buchtala and B. Sick, "Techniques for the fusion of symbolic rules in distributed organic systems," in Proceedings of the IEEE Mountain Workshop on Adaptive and Learning Systems (SMCals/06), Logan, 2006, pp. 85-90.
4. R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification. John Wiley & Sons, Chichester, New York, 2001.
5. M. H. Dunham, Data Mining: Introductory and Advanced Topics. Pearson Education, Upper Saddle River, 2003.
6. U. M. Fayyad, G. Piatetsky-Shapiro, and P. Smyth, "Knowledge discovery and data mining: Towards a unifying framework," in Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD 1996), Portland, 1996, pp. 82-88.
7. T. Poggio and F. Girosi, "A theory of networks for approximation and learning," Massachusetts Institute of Technology - Artificial Intelligence Laboratory & Center for Biological Information Procesing - Whitaker College," A.I. Memo No. 1140, C.B.I.P. Paper No. 31, 1989.
8. H. C. Andersen, A. Lotfi, and L. C. Westphal, "Comments on "Functional equivalence between radial basis function networks and fuzzy inference systems"," IEEE Transactions on Neural Networks, vol. 9, no. 6, pp. 1529-1531, 1998.
9. F. Schwenker, H. A. Kestler, and G. Palm, "Three learning phases for radial-basis-function networks," Neural Networks, vol. 14, no. 4-5, pp. 439-458, 2001.
10. O. Buchtala, P. Neumann, and B. Sick, "A strategy for an efficient training of radial basis function networks for classification applications," in Proceedings of the IEEE-INNS International Joint Conference on Neural Networks, Portland, vol. 2, 2003, pp. 1025-1030.
11. O. Buchtala, "Transformation von Radialen-Basisfunktionen-Netzen in Fuzzy Systeme," Master's thesis, University of Passau, Department of Mathematics and Computer Science, 2005.
12. C. M. Grinstead and J. L. Snell, Introduction to Probability, 2nd ed. American Mathematical Society, Providence, 1997.
13. O. Buchtala and B. Sick, "Functional knowledge exchange within an intelligent distributed system," in Proceedings of the 20th International Conference on Architecture of Computing Systems - System Aspects in Pervasive and Organic Computing (ARCS 2007), Zurich, 2007, (accepted - to appear).